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  • 1.
    Bayisa, Fekadu
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Kuljus, Kristi
    Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia.
    Johansson, Adam
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Bolin, David
    Department of Mathematical Sciences, Chalmers and University of Gothenburg, Gothenburg, Sweden.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Prediction of CT images from MR images with hidden Markov and random field models2016In: Proceedings of the 8th International Workshop on Spatio-Temporal Modelling / [ed] A. Iftimi, J. Mateu and F. Montes, 2016, p. 163-163Conference paper (Other academic)
  • 2.
    Bayisa, Fekadu L.
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Liu, Xijia
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Computed Tomography Image Estimation by Statistical Learning MethodsManuscript (preprint) (Other academic)
    Abstract [en]

    There is increasing interest in computed tomography (CT) image estimations from magnetic resonance (MR) images. The estimated CT images canbe utilised for attenuation correction, patient positioning, and dose planningin diagnostic and radiotherapy workflows. This study presents a statisticallearning method for CT image estimation. We have used predefined tissuetype information in a Gaussian mixture model to explore the estimation.The performance of our method was evaluated using cross-validation on realdata. In comparison with the existing model-based CT image estimationmethods, the proposed method has improved the estimation, particularly inbone tissues. Evaluation of our method shows that it is a promising methodto generate CT image substitutes for the implementation of fully MR-basedradiotherapy and PET/MRI applications.

  • 3.
    Bayisa, Fekadu
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Liu, Xijia
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Statistical learning in computed tomography image estimation2018In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 45, no 12, p. 5450-5460Article in journal (Refereed)
    Abstract [en]

    Purpose: There is increasing interest in computed tomography (CT) image estimations from magneticresonance (MR) images. The estimated CT images can be utilized for attenuation correction, patientpositioning, and dose planning in diagnostic and radiotherapy workflows. This study aims to introducea novel statistical learning approach for improving CT estimation from MR images and to compare theperformance of our method with the existing model-based CT image estimation methods.

    Methods: The statistical learning approach proposed here consists of two stages. At the trainingstage, prior knowledge about tissue types from CT images was used together with a Gaussian mixturemodel (GMM) to explore CT image estimations from MR images. Since the prior knowledge is notavailable at the prediction stage, a classifier based on RUSBoost algorithm was trained to estimatethe tissue types from MR images. For a new patient, the trained classifier and GMMs were used topredict CT image from MR images. The classifier and GMMs were validated by using voxel-leveltenfold cross-validation and patient-level leave-one-out cross-validation, respectively.

    Results: The proposed approach has outperformance in CT estimation quality in comparison withthe existing model-based methods, especially on bone tissues. Our method improved CT image estimationby 5% and 23% on the whole brain and bone tissues, respectively.

    Conclusions: Evaluation of our method shows that it is a promising method to generate CTimage substitutes for the implementation of fully MR-based radiotherapy and PET/MRI applications

  • 4.
    Bayisa, Fekadu
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Model-based Estimation of Computed Tomography Images2017Conference paper (Other academic)
  • 5.
    Bayisa, Fekadu
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Model-based Estimation of Computed Tomography Images2017Manuscript (preprint) (Other academic)
    Abstract [en]

    There is a growing interest to get a fully MR based radiotherapy. The most important development needed is to obtain improved bone tissue estimation. Existing model-based methods have performed poorly on bone tissues. This paper aims to obtainimproved estimation of bone tissues. Skew-Gaussian mixture model (SGMM) isproposed to further investigate CT image estimation from MR images. The estimation quality of the proposed model is evaluated using leave-one-out cross-validation method on real data. In comparison with the existing model-based approaches, the approach utilized in this paper outperforms in estimation of bone tissues, especiallyon dense bone tissues.

  • 6.
    Bayisa, Fekadu
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Zhou, Zhiyong
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Cronie, Ottmar
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Adaptive algorithm for sparse signal recovery2018Manuscript (preprint) (Other academic)
    Abstract [en]

    Spike and slab priors play a key role in inducing sparsity for sparse signal recovery. The use of such priorsresults in hard non-convex and mixed integer programming problems. Most of the existing algorithms to solve the optimization problems involve either simplifying assumptions, relaxations or high computational expenses. We propose a new adaptive alternating direction method of multipliers (AADMM) algorithm to directly solve the presented optimization problem. The algorithm is based on the one-to-onemapping property of the support and non-zero element of the signal. At each step of the algorithm, we update the support by either adding an index to it or removing an index from it and use the alternatingdirection method of multipliers to recover the signal corresponding to the updated support. Experiments on synthetic data and real-world images show that the proposed AADMM algorithm provides superior performance and is computationally cheaper, compared to the recently developed iterative convex refinement (ICR) algorithm.

  • 7.
    Brynolfsson, Patrik
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Wirestam, Ronnie
    Lund University.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. CJ Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, Netherlands.
    Combining phase and magnitude information for contrast agent quantification in dynamic contrast-enhanced MRI using statistical modeling2015In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 74, no 4, p. 1156-1164Article in journal (Refereed)
    Abstract [en]

    Purpose: The purpose of this study was to investigate, using simulations, a method for improved contrast agent (CA) quantification in DCE-MRI.

    Methods: We developed a maximum likelihood estimator that combines the phase signal in the DCE-MRI image series with an additional CA estimate, e.g. the estimate obtained from magnitude data. A number of simulations were performed to investigate the ability of the estimator to reduce bias and noise in CA estimates. Noise levels ranging from that of a body coil to that of a dedicated head coil were investigated at both 1.5T and 3T.

    Results: Using the proposed method, the root mean squared error in the bolus peak was reduced from 2.24 to 0.11 mM in the vessels and 0.16 to 0.08 mM in the tumor rim for a noise level equivalent of a 12-channel head coil at 3T. No improvements were seen for tissues with small CA uptake, such as white matter.

    Conclusion: Phase information reduces errors in the estimated CA concentrations. A larger phase response from higher field strengths or higher CA concentrations yielded better results. Issues such as background phase drift need to be addressed before this method can be applied in vivo.

  • 8.
    Cronie, Ottmar
    et al.
    Mathematical Sciences, Chalmers University of Technology and University of Gothenburg.
    Nyström, Kenneth
    SLU, Department of Forest Resource Management.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Spatiotemporal Modeling of Swedish Scots Pine Stands2013In: Forest Science, ISSN 0015-749X, E-ISSN 1938-3738, Vol. 59, no 5, p. 505-516Article in journal (Refereed)
    Abstract [en]

    The growth-interaction (GI) process is employed for the spatiotemporal modelling of measurements of locations and radii at breast height made at three different time points of the individual trees in ten Scots pine (Pinus sylvestris) plots from the Swedish NFI. The GI-process places trees at random locations in the study region and assigns sizes to the trees, which interact and grow with time. It has been used to model plots in previous studies and to improve the fit we suggest some modifications: a different location assignment strategy and a different open-growth (growth under negligible competition) function. We believe that the calibration data contain trees that are too small to reflect the open-growth properly, which primarily affects the carrying capacity parameter. To better represent the open-growth of Scots pines, we evaluate the open-growth from a separate set of data (size and age measurements of older and larger single Scots pines). A linear relationship is found between the plot's estimated site indices and the sizes, and this is exploited in the estimation of the carrying capacity. We finally estimate the remaining GI-process parameters and test the goodness-of-fit on simulated predictions from the fitted model.

  • 9.
    Cronie, Ottmar
    et al.
    Chalmers University of Technology.
    Yu, Jun
    SLU, Centre of Biostochastics.
    Maximum likelihood estimation in a discretely observed immigration-death process2010Report (Other academic)
    Abstract [en]

    In order to find the maximum likelihood (ML) estimator of the parameter pair governing the immigration-death process (a continuous time Markov chain) we derive its transition probabilities. The likelihood maximisation problem is reduced from two dimensions to one dimension. We also show the consistency and the asymptotic normality of the ML-estimator under an equidistant sampling scheme, given that the parameter pair lies in some compact subset of the positive part of the real plane. We thereafter evaluate, numerically, the behaviour of the estimator and we finally see how our ML-estimation can be applied to the so-called Renshaw-Särkkä growth interaction model; a spatio-temporal point process with time dependent interacting marks in which the immigration-death process controls the arrivals of new marked points as well as their potential life-times.

  • 10.
    Cronie, Ottmar
    et al.
    Stochastics, CWI, Amsterdam, The Netherlands.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    The discretely observed immigration-death process: Likelihood inference and spatiotemporal applications2016In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 45, no 18, p. 5279-5298Article in journal (Refereed)
    Abstract [en]

    We consider a stochastic process, the homogeneous spatial immigration-death (HSID) process, which is a spatial birth-death process with as building blocks (i) an immigration-death (ID) process (a continuous-time Markov chain) and (ii) a probability distribution assigning iid spatial locations to all events. For the ID process, we derive the likelihood function, reduce the likelihood estimation problem to one dimension, and prove consistency and asymptotic normality for the maximum likelihood estimators (MLEs) under a discrete sampling scheme. We additionally prove consistency for the MLEs of HSID processes. In connection to the growth-interaction process, which has a HSID process as basis, we also fit HSID processes to Scots pine data.

  • 11.
    Cronie, Ottmar
    et al.
    Chalmers University of Technology, Göteborg.
    Yu, Jun
    Centre of Biostochatics, SLU.
    Nyström, Kenneth
    Forest Resource Management, SLU.
    Spatio-Temporal Modelling of Swedish Scots Pine Stands2011Report (Other academic)
    Abstract [en]

    Considering measurements of locations and radii at breast height made at three different time points of the individual trees in ten Swedish Scots pine plots, we employ the so called growth-interaction (GI) process for the spatio-temporal modelling of the plots. The GI-process places trees at random locations in the study region and assigns radii (sizes) to the trees, which interact and grow with time. It has been used to model Scots pine plots in previous studies, and to improve the fit we suggest some modifications of the model: A different location assignment strategy and a different function for the open-growth (growth in absence of competition). We believe also that the space-time data contain too small trees to reflect the open-growth properly, which primarily affectsthe carrying capacity parameter. We evaluate the open-growth froma separate set of data which consists of size and age measurements ofolder and larger single Scots pines. This data set better represents the open-growth of Scots pines than the space-time data sets. A linear relationship is found between the estimated site indexes of the plots and the sizes, and this relationship is exploited in the estimation of the carrying capacity. For each of the ten space-time data sets (plots) we estimate the remaining parameters of the GI-process and finally, by means of some Monte Carlo tests, we test the goodness-of-fit of simulated predictions from the fitted model.

  • 12.
    Englund, Göran
    et al.
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Sjödin, Henrik
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Bonsall, Michael
    Oxford University.
    Cianelli, Lorenzo
    Oregon State University.
    Frank, Kenneth
    Bedford Institute of Oceanography.
    Heino, Mikko
    University of Bergen.
    Janssen, Arne
    University of Amsterdam.
    Leonardsson, Kjell
    Swedish University of Agricultural Science.
    van der Meer, Jaap
    Royal Netherlands Institute for Sea Research.
    Nachman, Gösta
    Copenhagen University.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Density dependence induced by the spatial covariance between predators and preyManuscript (preprint) (Other academic)
  • 13.
    Garpebring, Anders
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Brynolfsson, Patrik
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Yu, Jun
    Sveriges lantbruksuniversitet, Centre of Biostochastiscs.
    Wirestam, Ronnie
    Lunds universitet, Medicinsk strålningsfysik.
    Johansson, Adam
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Asklund, Thomas
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Uncertainty estimation in dynamic contrast-enhanced MRI2013In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 69, no 4, p. 992-1002Article in journal (Refereed)
    Abstract [en]

    Using dynamic contrast-enhanced MRI (DCE-MRI), it is possible to estimate pharmacokinetic (PK) parameters that convey information about physiological properties, e.g., in tumors. In DCE-MRI, errors propagate in a nontrivial way to the PK parameters. We propose a method based on multivariate linear error propagation to calculate uncertainty maps for the PK parameters. Uncertainties in the PK parameters were investigated for the modified Kety model. The method was evaluated with Monte Carlo simulations and exemplified with in vivo brain tumor data. PK parameter uncertainties due to noise in dynamic data were accurately estimated. Noise with standard deviation up to 15% in the baseline signal and the baseline T1 map gave estimated uncertainties in good agreement with the Monte Carlo simulations. Good agreement was also found for up to 15% errors in the arterial input function amplitude. The method was less accurate for errors in the bolus arrival time with disagreements of 23%, 32%, and 29% for Ktrans, ve, and vp, respectively, when the standard deviation of the bolus arrival time error was 5.3 s. In conclusion, the proposed method provides efficient means for calculation of uncertainty maps, and it was applicable to a wide range of sources of uncertainty.

  • 14.
    Garpebring, Anders
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Brynolfsson, Patrik
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Wirestam, Ronnie
    Radiofysik, Lunds Universitet.
    Johansson, Adam
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Thomas, Asklund
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Uncertainty Maps in Dynamic Contrast-Enhanced MRI2012Conference paper (Refereed)
  • 15.
    Garpebring, Anders
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Wirestam, Ronnie
    Yu, Jun
    SLU, Centre of Biostochastics.
    Asklund, Thomas
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Phase-based arterial input functions in humans applied to dynamic contrast-enhanced MRI: potential usefulness and limitations2011In: Magnetic Resonance Materials in Physics, Biology and Medicine, ISSN 0968-5243, E-ISSN 1352-8661, Vol. 24, no 4, p. 233-245Article in journal (Refereed)
    Abstract [en]

    Object: Phase-based arterial input functions (AIFs) provide a promising alternative to standard magnitude-based AIFs, for example, because inflow effects are avoided. The usefulness of phase-based AIFs in clinical dynamic contrast-enhanced MRI (DCE-MRI) was investigated, and relevant pitfalls and sources of uncertainty were identified.

    Materials and methods: AIFs were registered from eight human subjects on, in total, 21 occasions. AIF quality was evaluated by comparing AIFs from right and left internal carotid arteries and by assessing the reliability of blood plasma volume estimates.

    Results: Phase-based AIFs yielded an average bolus peak of 3.9 mM and a residual concentration of 0.37 mM after 3 min, (0.033 mmol/kg contrast agent injection). The average blood plasma volume was 2.7% when using the AIF peak in the estimation, but was significantly different (p < 0.0001) and less physiologically reasonable when based on the AIF tail concentration. Motion-induced phase shifts and accumulation of contrast agent in background tissue regions were identified as main sources of uncertainty.

    Conclusions: Phase-based AIFs are a feasible alternative to magnitude AIFs, but sources of errors exist, making quantification difficult, especially of the AIF tail. Improvement of the technique is feasible and also required for the phase-based AIF approach to reach its full potential.

  • 16.
    Henriksson, Anna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Wardle A., David
    Swedish University of Agriculture Sciences, Department of Forest Vegetation Ecology.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Englund, Göran
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Weighted species richness outperforms species richness as predictor of biotic resistance2016In: Ecology, ISSN 0012-9658, E-ISSN 1939-9170, Vol. 97, no 1, p. 262-271Article in journal (Refereed)
    Abstract [en]

    The species richness hypothesis, which predicts that species-rich communities should be better at resisting invasions than species-poor communities, has been empirically tested many times and often poorly supported. In this paper we contrast the species richness hypothesis with four alternative hypotheses with the aim of finding better descriptors of invasion resistance. These alternative hypotheses state that resistance to invasions is determined by abiotic conditions, community saturation (i.e., the number of resident species relative to the maximum number of species that can be supported), presence/absence of key species, or weighted species richness. Weighted species richness is a weighted sum of the number of species, where each species' weight describes its contribution to resistance. We tested these hypotheses using data on the success of 571 introductions of four freshwater fish species into lakes throughout Sweden (i.e., Arctic char (Salvelinus alpinus), tench (Tinca tinca), zander (Sander lucioperca), and whitefish (Coregonus lavaretus)). We found that the weighted species richness best predicted invasion success. The weights describing the contribution of each resident species to community resistance varied considerably in both strength and sign. Positive resistance weights, which indicate that species repel invaders, were as common as negative resistance weights, which indicate facilitative interactions. This result can be contrasted with the implicit assumption of the original species richness hypothesis, that all resident species have negative effects on invader success. We argue that this assumption is unlikely to be true in natural communities, and thus that we expect that weighted species richness is a better predictor of invader success than the actual number of resident species.

  • 17.
    Henriksson, Anna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Wardle, David A.
    Englund, Göran
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Biotic resistance in freshwater fish communities: species richness, saturation or species identity?2015In: Oikos, ISSN 0030-1299, E-ISSN 1600-0706, Vol. 124, no 8, p. 1058-1064Article in journal (Refereed)
    Abstract [en]

    Some communities are susceptible to invasions and some are not. Why? Elton suggested in 1958 that the ability of the community to withstand invading species - its biotic resistance - depends on the number of resident species. Later contributors have emphasized the habitat's ability to support species, as well as the contribution of individual species to the resistance. In this study we use information from 184 introductions of Arctic char into Swedish lakes to study both abiotic and biotic aspects of the resident community's ability to resist introductions. We find that the best model included the proportion of forest cover and the proportion of agricultural land cover in the watershed in combination with the presence versus absence of northern pike. Thus, the most important biotic factor to explain the outcome of introductions of Arctic char is the presence of northern pike, a large piscivore. This means that one single species explains the outcome of the introductions better than does the species richness or the saturation level of the community.

  • 18.
    Hildeman, Anders
    et al.
    Department of Mathematical Sciences, Chalmers University of Technology, Sweden.
    Bolin, David
    Department of Mathematical Sciences, Chalmers University of Technology, Sweden.
    Wallin, Jonas
    Department of Statistics, Lund University.
    Johansson, Adam
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Asklund, Thomas
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Hildeman, A., Bolin, D., Wallin, J., Johansson, A., Nyholm, T., Asklund, T., and Yu, J. Whole-brain substitute CT generation using Markov random field mixture models.2016Manuscript (preprint) (Other academic)
    Abstract [en]

    Computed tomography (CT) equivalent information is needed for attenuation correction in PET imaging and for dose planning in radiotherapy. Prior work has shown that Gaussian mixture models can be used to generate a substitute CT (s-CT) image from a specific set of MRI modalities. This work introduces a more flexible class of mixture models for s-CT generation, that incorporates spatial dependency in the data through a Markov random field prior on the latent field of class memberships associated with a mixture model. Furthermore, the mixture distributions are extended from Gaussian to normal inverse Gaussian (NIG), allowing heavier tails and skewness. The amount of data needed to train a model for s-CT generation is of the order of 10^8 voxels. The computational efficiency of the parameter estimationand prediction methods are hence paramount, especially when spatial dependency is included in the models. A stochastic Expectation Maximization (EM) gradient algorithm is proposed in order to tackle this challenge. The advantages of the spatial model and NIG distributions are evaluated with a cross-validation study based ondata from 14 patients. The study show that the proposed model enhances the predictive quality of the s-CT images by reducing the mean absolute error with 17.9%. Also, the distribution of CT values conditioned on the MR images are better explainedby the proposed model as evaluated using continuous ranked probability scores.

  • 19.
    Jiao, Xiang
    et al.
    College of Mechanical and Electronic Engineering, Nanjing Forestry University.
    Zhang, Huichun
    College of Mechanical and Electronic Engineering, Nanjing Forestry University.
    Zheng, Jiaqiang
    College of Mechanical and Electronic Engineering, Nanjing Forestry University.
    Yin, Yue
    College of Mechanical and Electronic Engineering, Nanjing Forestry University.
    Wang, Guosu
    College of Mechanical and Electronic Engineering, Nanjing Forestry University.
    Chen, Ying
    College of Forestry, Nanjing Forestry University.
    Ge, Yufeng
    Department of Biological Systems Engineering, University of Nebraska-Lincoln.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Comparative analysis of nonlinear growth curve models for Arabidopsis thaliana rosette leaves2018In: Acta Physiologiae Plantarum, ISSN 0137-5881, E-ISSN 1861-1664, Vol. 40, no 6, article id 114Article in journal (Refereed)
    Abstract [en]

    As a model organism, modeling and analysis of the phenotype of Arabidopsis thaliana (A. thaliana) leaves for a given genotype can help us better understand leaf growth regulation. A. thaliana leaves growth trajectories are to be nonlinear and the leaves contribute most to the above-ground biomass. Therefore, analysis of their change regulation and development of nonlinear growth models can better understand the phenotypic characteristics of leaves (e.g., leaf size) at different growth stages. In this study, every individual leaf size of A. thaliana rosette leaves was measured during their whole life cycle using non-destructive imaging measurement. And three growth models (Gompertz model, logistic model and Von Bertalanffy model) were analyzed to quantify the rosette leaves growth process of A. thaliana. Both graphical (plots of standardized residuals) and numerical measures (AIC, R2 and RMSE) were used to evaluate the fitted models. The results showed that the logistic model fitted better in describing the growth of A. thaliana leaves compared to Gompertz model and Von Bertalanffy model, as it gave higher R2 and lower AIC and RMSE for the leaves of A. thaliana at different growth stages (i.e., early leaf, mid-term leaf and late leaf).

  • 20.
    Johansson, Adam
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Yu, Jun
    SLU, Centre of Biostochastics.
    Asklund, Thomas
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Voxel-wise uncertainty in CT substitute derived from MRI2012In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 39, no 6, p. 3283-3290Article in journal (Refereed)
    Abstract [en]

    Purpose: In an earlier work, we demonstrated that substitutes for CT images can be derived from MR images using ultrashort echo time (UTE) sequences, conventional T2 weighted sequences, and Gaussian mixture regression (GMR). In this study, we extend this work by analyzing the uncertainties associated with the GMR model and the information contributions from the individual imaging sequences.

    Methods: An analytical expression for the voxel-wise conditional expected absolute deviation (EAD) in substitute CT (s-CT) images was derived. The expression depends only on MR images and can thus be calculated along with each s-CT image. The uncertainty measure was evaluated by comparing the EAD to the true mean absolute prediction deviation (MAPD) between the s-CT and CT images for 14 patients. Further, the influence of the different MR images included in the GMR model on the generated s-CTs was investigated by removing one or more images and evaluating the MAPD for a spectrum of predicted radiological densities.

    Results: The largest EAD was predicted at air-soft tissue and bone-soft tissue interfaces. The EAD agreed with the MAPD in both these regions and in regions with lower EADs, such as the brain. Two of the MR images included in the GMR model were found to be mutually redundant for the purpose of s-CT generation.

    Conclusions: The presented uncertainty estimation method accurately predicts the voxel-wise MAPD in s-CT images. Also, the non-UTE sequence previously used in the model was found to be redundant.

  • 21.
    Karlsson, Stefan
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF).
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Mathematical statistics.
    Estimation of surface electromyogram spectral alteration using reduced-order autoregressive model2000In: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 38, p. 520-527Article in journal (Refereed)
    Abstract [en]

    A new method is proposed, based on the pole phase angle (PPA) of a second-order autoregressive (AR) model, to track spectral alteration during localised muscle fatigue when analysing surface myo-electric (ME) signals. Both stationary and non-stationary, simulated and real ME signals are used to investigate different methods to track spectral changes. The real ME signals are obtained from three muscles (the right vastus lateralis, rectus femoris and vastus medialis) of six healthy male volunteers, and the simulated signals are generated by passing Gaussian white-noise sequences through digital filters with spectral properties that mimic the real ME signals. The PPA method is compared, not only with spectra-based methods, such as Fourier and AR, but also with zero crossings (ZCs) and the first AR coefficient that have been proposed in the literature as computer efficient methods. By comparing the deviation (dev), in percent, between the linear regression of the theoretical and estimated mean frequencies of the power spectra for simulated stationary (s) and non-stationary (ns) signals, in general, it is found that the PPA method (dev(s) = 4.29; dev(ns) = 1.94) gives a superior performance to ZCs (dv(s) = 8.25) and the first AR coefficient (4.18<dev(s)<21.8; 0.98<dev(ns)<4.36) but performs slightly worse than spectra-based methods (0.33<dev(s)<0.79; 0.41<dev(ns)<1.07). However, the PPA method has the advantage that it estimates spectral alteration without calculating the spectra and therefore allows very efficient computation.

  • 22.
    Karlsson, Stefan
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Mathematical statistics.
    Time-frequency analysis of surface EMG signals using wavelets1996In: Proceedings of the 11th Congress of the International Society of Electrophysiology and Kinesiology, 1996, p. 135-137Conference paper (Refereed)
  • 23.
    Karlsson, Stefan
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Mathematical statistics.
    Akay, Metin
    Thayer School of Engineering, Dartmouth College,.
    Time-Frequency Analysis of Myoelectric Signals During Dynamic Contractions: A Comparative Study2000In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 47, no 2, p. 228-238Article in journal (Refereed)
    Abstract [en]

    In this paper, we introduce the nonstationary signal analysis methods to analyze the myoelectric (ME) signals during dynamic contractions by estimating the time-dependent spectral moments. The time-frequency analysis methods including the short-time Fourier transform, the Wigner–Ville distribution, the Choi–Williams distribution, and the continuous wavelet transform were compared for estimation accuracy and precision on synthesized and real ME signals. It is found that the estimates providedby the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets. In addition, ME signals from four subjects during three different tests (maximum static voluntary contraction, ramp contraction, and repeated isokinetic contractions) were also examined.

  • 24.
    Karlsson, Stefan
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Mathematical statistics.
    Äkay, Metin
    Thayer School of Engineering, Dartmouth College.
    Enhancement of spectral analysis of myoelectric signals during static contractions using wavelet methods1999In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 46, no 6, p. 670-684Article in journal (Refereed)
    Abstract [en]

    In this paper, we introduce wavelet packets as an alternative method for spectral analysis of surface myoelectric(ME) signals. Both computer synthesized and real ME signals are used to investigate the performance. Our simulation results show that wavelet packet estimate has slightly less mean squareerror (MSE) than Fourier method, and both methods perform similarly on the real data. Moreover, wavelet packets give us some advantages over the traditional methods such as multiresolutionof frequency, as well as its potential use for effecting time-frequency decomposition of the nonstationary signals such as the ME signals during dynamic contractions. We also introduce wavelet shrinkage method for improving spectral estimates bysignificantly reducing the MSE’s for both Fourier and wavelet packet methods.

  • 25.
    Kuljus, Kristi
    et al.
    University of Tartu, Estonia.
    Bayisa, Fekadu
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Bolin, David
    Chalmers University of Technology, Sweden.
    Lember, Jüri
    University of Tartu, Estonia.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Comparison of hidden Markov chain models and hidden Markov random field models in estimation of computed tomography images2017Manuscript (preprint) (Other academic)
    Abstract [en]

    There is an interest to replace computed tomography (CT) images withmagnetic resonance (MR) images for a number of diagnostic and therapeuticworkflows. In this article, predicting CT images from a number of magnetic resonance imaging (MRI) sequences using regression approach isexplored. Two principal areas of application for estimated CT images aredose calculations in MRI based radiotherapy treatment planning and attenuationcorrection for positron emission tomography (PET)/MRI. Themain purpose of this work is to investigate the performance of hidden Markov (chain) models (HMMs) in comparison to hidden Markov random field (HMRF) models when predicting CT images of head. Ourstudy shows that HMMs have clear advantages over HMRF models in this particular application. Obtained results suggest that HMMs deservea further study for investigating their potential in modeling applications where the most natural theoretical choice would be the class of HMRFmodels.

  • 26.
    Kuljus, Kristi
    et al.
    University of Tartu, Estonia.
    Bayisa, Fekadu
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Bolin, David
    Department of Mathematical Sciences, Chalmers University of Technology, Sweden.
    Lember, Jüri
    University of Tartu, Estonia.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Comparison of hidden Markov chain models and hidden Markov random field models in estimation of computed tomography images2018In: Communications in Statistics: Case Studies, Data Analysis and Applications, ISSN 2373-7484, Vol. 4, no 1, p. 46-55Article in journal (Refereed)
    Abstract [en]

    Two principal areas of application for estimated computed tomography (CT) images are dose calculations in magnetic resonance imaging (MRI) based radiotherapy treatment planning and attenuation correction for positron emission tomography (PET)/MRI. The main purpose of this work is to investigate the performance of hidden Markov (chain) models (HMMs) in comparison to hidden Markov random field (HMRF) models when predicting CT images of head. Obtained results suggest that HMMs deserve a further study for investigating their potential in modeling applications, where the most natural theoretical choice would be the class of HMRF models.

  • 27.
    Li, He
    et al.
    Hangzhou University, Department of Athletics.
    Yu, Jun
    Hangzhou University, Department of Mathematics.
    Research on developmental strategy of athletic sports in Zhejiang Province: Volleyball1988In: Journal of Zhejiang Sports Science, ISSN 1004-3624, Vol. 8, p. 143-151Article in journal (Refereed)
  • 28.
    Löfgren, Stefan
    et al.
    Institutionen för vatten och miljö, SLU.
    Fröberg, Mats
    Institutionen för vatten och miljö, SLU.
    Nisell, Jakob
    SGU.
    Yu, Jun
    Centre of Biostochastics, SLU.
    Ranneby, Bo
    Centre of Biostochastics, SLU.
    N- och P-halterna i skog, myr och fjäll hösten 2011 i Dalälven, Viskan, Ätran, Nissan och Lagan: projekt för att förbättra skattningarna av typhalter inför PLC62012Report (Other academic)
    Abstract [en]

    As part of earlier pilot projects (SMED Report No. 52:2011 and SMED report 100:2011) and based on data from the national forest survey (RIS) and satellite scenes, the statistical method Probabilistic classifier was used for classifying the forest status of forest land, peat land and mountain areas. Riparian forests were defined based on the virtual streamwater network (VIVAN). Based on data from 200 randomly selected headwaters of the rivers Dalälven, Viskan, Ätran, Nissan and Lagan and the forest status in riparian and more remote forests, models were created to estimate spring and summer type concentrations of N and P in stream water. The explanation power of the Tot-N and Tot-P models was significantly higher than those used in connection with PLC5 both spring and summer.

    Within this project, water samples collected in November 2011 from the 200 randomly selected headwaters of river Dalälven and in southwestern Sweden were analyzed. The measured concentrations were compared with the summer and spring concentrations and based on new methodology (Bayesian Model Averages) new models were created to estimate the Tot-N and Tot-P type concentrations in stream water in spring, summer and in early and late autumn.

    The results show that the explanation power by the models is tangibly higher all seasons for Tot-N and Tot-P (R2tot-N=0.46-0.66 respective R2tot-P=0.27-0.40) compared with those used in northern Sweden in PLC5 (R2tot-N=0.25 respective R2tot-P=0.11). The study indicates that the PLC5 type concentrations strongly underestimate the leaching from forests of both Tot-N (25-140%) and Tot-P (63-175%) at the Swedish West Coast, while the results from the Dalälven area indicate an overestimation spring and late autumn (23-36%) and underestimation summer and autumn (19-22%) as regards Tot-N. The modells indicate that forest growth, the share of clearfellings and wetlands within the catchments are the most important factors for the type concentrations. The type concentrations used in PLC5 cannot uncritically be used for e.g. source apportionments or as basis for N and P retention estimates from the headwaters to the sea. For such assessments, type concentrations based on models with higher precision, e.g. those presented here, must be used.

    Bearing in mind the generally high high water discharge during spring and autumn and its large influence on the transport calculations (= water discharge x concentration) there are good reasons to take into account the spatial and seasonal concentration variations in the source apportionments by improving the type concentrations of N and P. Similar surveys and assessments as in this study should therefore be performed in southeast and northern Sweden in order to improve the estimates of the N and P leaching from forests, wetlands and alpine areas also in those regions.

  • 29.
    Löfgren, Stefan
    et al.
    Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden .
    Fröberg, Mats
    Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden .
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Nisell, Jakob
    Geological Survey of Sweden, Uppsala, Sweden.
    Ranneby, Bo
    Centre of Biostochastics, Swedish University of Agricultural Sciences, Umeå, Sweden .
    Water chemistry in 179 randomly selected Swedish headwaterstreams related to forest production, clear-felling and climate2014In: Environmental Monitoring & Assessment, ISSN 0167-6369, E-ISSN 1573-2959, Vol. 186, no 12, p. 8907-8928Article in journal (Refereed)
    Abstract [en]

    From a policy perspective, it is important to understand forestry effects on surface waters from a landscape perspective. The EU Water Framework Directive demands remedial actions if not achieving good ecological status. In Sweden, 44 % of the surface water bodies have moderate ecological status or worse. Many of these drain catchments with a mosaic of managed forests. It is important for the forestry sector and water authorities to be able to identify where, in the forested landscape, special precautions are necessary. The aim of this study was to quantify the relations between forestry parameters and headwater stream concentrations of nutrients, organic matter and acid-base chemistry. The results are put into the context of regional climate, sulphur and nitrogen deposition, as well as marine influences. Water chemistry was measured in 179 randomly selected headwater streams from two regions in southwest and central Sweden, corresponding to 10 % of the Swedish land area. Forest status was determined from satellite images and Swedish National Forest Inventory data using the probabilistic classifier method, which was used to model stream water chemistry with Bayesian model averaging. The results indicate that concentrations of e.g. nitrogen, phosphorus and organic matter are related to factors associated with forest production but that it is not forestry per se that causes the excess losses. Instead, factors simultaneously affecting forest production and stream water chemistry, such as climate, extensive soil pools and nitrogen deposition, are the most likely candidates The relationships with clear-felled and wetland areas are likely to be direct effects.

  • 30.
    Löfgren, Stefan
    et al.
    Institutionen för vatten och miljö, SLU.
    Nisell, Jakob
    Institutionen för vatten och miljö, SLU.
    Yu, Jun
    Centre of Biostochastics, SLU.
    Ranneby, Bo
    Centre of Biostochastics, SLU.
    Förbättrade skattningar av N- och P-förlusterna från skog, myr och fjäll inför PLC6: pilotprojekt2011Report (Other academic)
    Abstract [sv]

    Inom ramen för detta pilotprojekt har data från riksinventeringen av skog (RIS) och satellitscener använts för att med den statistiska metoden Probabilistic Classifier klassificera skogstillståndet på skogs- och myrmark inklusive fjäll. Vattendragsnära skog har definierats utgående från ett virtuellt nätverksbildat vattendragsnät (VIVAN). Baserat på ca 200 slumpmässigt utvalda källvattendrag i Dalälven, Viskan, Ätran, Nissan och Lagan har därefter modeller skapats för att skatta typhalterna för N och P i bäckvattnet utgående från skogstillståndet i bäcknära och mer avlägsen skog.

    Modellernas förklaringsgrad för Tot-N (r2=0,60) och Tot-P (r2=0,31) är betydligt bättre än de som användes i norra Sverige inom ramen för PLC5 (r2=0,25 respektive (r2=0,11), vilket tyder på att det dels föreligger samband mellan avrinningsområdets egenskaper och N och P halterna och dels att probabilistisk klassning är en användbar metod för att skatta dessa egenskaper. Ytterligare en förbättring jämfört med PLC5 är att Tot-N och Tot-P i södra Sverige samt oorganiskt kväve och fosfat inte längre behöver hanteras som konstanter. Modellerna för de oorganiska fraktionerna är dock osäkra.

    Typhalterna är betydligt högre än de som användes inom PLC5. Orsaken till detta är att analysresultaten från de slumpmässigt utvalda vattendragen visar att sommartid kan närsalthalterna i skogs- och myrbäckar vara betydligt högre än medel- och medianvärden från längre tidsperioder, som även innehåller säsongsoch mellanårlig variation. De presenterade typhalterna kan därför inte okritiskt användas för t.ex. källfördelningsmodellering. För det krävs modeller baserade på vattenkemisk information även från andra årstider.

    Vi har stora möjligheter att ytterligare förbättra modellernas både rumsliga och tidsmässiga precision och för att använda metodiken över hela Sverige. De förbättringar som krävs är då främst tillgång till enhetliga satellitdata från ett begränsat tidsfönster för framtagande av differensbilder (används för klassning av löv) och probabilistisk klassificering, en höjddatabas med högre rumslig (x-, y- och z-led) upplösning och förnyad simulering av ett virtuellt vattendragsnät alternativt en förbättrad vattendragskarta samt upprepad provtagning (data bör finnas från vår, sommar, höst och vinter) av slumpmässigt utvalda skogs- och myrvattendrag för förbättrad skattning av den temporala variationen i typhalterna. Den teknikutveckling som krävs på satellitscen- och höjddatabassidan bör finnas tillgänglig inom en treårsperiod, medan det inte finns medel avsatta för provtagning och analys av slumpmässigt insamlade prover från olika årstider.

  • 31.
    Löfgren, Stefan
    et al.
    Institutionen för vatten och miljö, SLU.
    Ranneby, Bo
    Centre of Biostochastics, SLU.
    Ekström, Magnus
    Centre of Biostochastics, SLU.
    Yu, Jun
    Centre of Biostochastics, SLU.
    Naturliga bakgrundshalter av bly, zink och arsenik i Svenska ytvatten baserat på metallernas haltvariation i morän och sedimentära jordar: implikationer för EU:s ramdirektiv för vatten och nationella miljömål2007Report (Other academic)
    Abstract [en]

    In the autumn 2006, lakes and running waters should be classified according to the EU water framework directive (2000/60/EU), which successively is implemented into the Swedish Environmental Act. Surface water monitoring should be in operation and environmental action plans, based on environmental assessments, should be in force at catchment level. The aim is to achieve “Good ecological status” in 2015. For each lake and running water, type specific reference conditions should be determined with regard to hydromorphological, physical-chemical and biological parameters. The reference status should represent conditions without human influences.

    The aim of this project was to develop models for estimating reference levels on the Pb, Zn and As concentrations in Swedish lakes based on the natural prerequisites regarding geology, vegetation, hydrology and surface water chemistry. Environmental authorities should be able to use the models in assessments demanded by the EU water framework directive and coupled to the national goals “Living lakes and streams” and “Non-toxic environment”.

    Based on the results from the year 2000 Swedish national lake survey, the geochemical and biogeochemical surveys of the Swedish Geological Survey, official statistics of climate, topography, land use etc., statistical models have been developed in order to estimate the natural background levels of Pb, Zn and As in lakes with catchments dominated by forests, mires and/or alpine ecosystems. The models are based on data from 644 lakes and approximately 28 000 geochemical observations. Multiple linear regressions were used for creating the models. For Pb and Zn, the least squares estimation method was used, while a robust estimation method was used for As (e.g. the robust fit is minimally influenced by outliers in the independent variables space, in the response space, or in both). Detailed analyses of the statistical prerequisites were performed and the established models fulfil the theoretical criterions necessary for the chosen techniques. The variations in Pb, Zn and As concentrations can to a large extent, 71%, 65% and 54%, respectively, be explained by lake internal factors with coupling to the humus levels (TOC) and acidity status (pH). In addition, the lake metals concentrations seem to be influenced by the accumulated atmospheric deposition of metals and acidifying compounds.

    By creating a second type of models, where geochemical and biogeochemical parameters were forced into the models, the degrees of explanation increased by 3, 7 and 3 percentage units for Pb, Zn and As, respectively. This marginal explanation increase indicates that the national lake survey is a weak tool for analysing the geochemical influences on the metal concentrations in surface waters. The lakes are randomly selected and it is only by chance some few lakes, with high metal concentrations in the water due to elevated metal concentrations in the soils, are sampled. In most of the objects, the humus and pH levels overshadow the geochemistry influence since metal concentrations in soils are generally low.

    Locally and in areas with elevated metal concentrations in the soils, other studies have demonstrated a correlation between the geochemistry and the surface water concentrations of metals. Hence, there is still a need for assessments studying at what metal levels in the soils the geochemistry is of importance for the metal concentrations in surface waters. Therefore, we suggest the Swedish Geological Survey to initiate such a project focusing on studies in areas with naturally occurring high metal concentrations in the soils and where small headwater streams are the aquatic response systems.

  • 32.
    Löthgren, Pia
    et al.
    Biostokastikum, SLU.
    Yu, Jun
    Biostokastikum, SLU.
    Maximum likelihood estimation of the distributional parameters of the magnitude and phase in magnetic resonance spectroscopy signals2012Conference paper (Refereed)
  • 33.
    Löthgren, Pia
    et al.
    Biostokastikum, SLU.
    Yu, Jun
    Biostokastikum, SLU.
    Maximum likelihood estimation of the parameters of a modified Rice distribution2010Conference paper (Refereed)
  • 34.
    Ranneby, Bo
    et al.
    SLU, Centre of Biostochastics.
    Yu, Jun
    SLU, Centre of Biostochastics.
    Classification of Agricultural Crops and Quality Assessment Using Multispectral and Multitemporal Images2003Report (Other academic)
    Abstract [en]

    In this paper, a new approach for classification of multitemporal satellite data sets, combining multispectral and change detection techniques is proposed. The algorithm is based on the nearest neighbor method and derived in order to optimize the average probability for correct classification, i.e. each class is equally important. The new algorithm was applied to a study area where satellite images (SPOT and Landsat TM) from different seasons over a year were used. It showed that using five seasonal images can substantially improve the classification accuracy compared to using one single image. As an real application to a large scale, the approach was applied to the Dalälven's catchment area. As the distributions for different classes are highly overlapping it is not possible to get satisfactory accuracy at pixel level. In stead it is necessary to introduce a new concept, pixel-wise probabilistic classifiers. The pixel-wise vectors of probabilities can be used to judge how reliablea traditional classification is and to derive measures of the uncertainty (entropy) for the individual pixels. The probabilistic classifier gives also unbiased area estimates over arbitrary areas. It has been tested on two test sites of arable land with different characteristics.

  • 35.
    Ranneby, Bo
    et al.
    SLU, Centre of Biostochastics.
    Yu, Jun
    SLU, Centre of Biostochastics.
    Estimation of WTP with point and self-selected interval responses2011In: Modern cost-benefit analysis of hydropower conflicts / [ed] Per-Olov Johansson och Bengt Kriström, Edward Elgar Publishing, 2011, p. 65-75Chapter in book (Refereed)
  • 36.
    Ranneby, Bo
    et al.
    SLU, Centre of Biostochastics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics. SLU, Centre of Biostochastics.
    Nonparametric and probabilistic classification using NN-balls with environmental and remote sensing applications2011In: Advances in Directional and Linear Statistics: A Festschrift for Sreenivasa Rao Jammalamadaka / [ed] M.T. Wells & A. Sengupta, Heidelberg: Physica Verlag, 2011, p. 201-216Chapter in book (Refereed)
    Abstract [en]

    National and international policies today require environmental follow-upsystems that detect, in a quality assured way, changes over time in land use and landscape indicators. Questions related to environmental health and spatial patterns call for new statistical tools.We present in this chapter some new developments on the classification of land use by using multispectral and multitemporal satellite images, based on techniques of nearest neighbour balls. The probabilistic classifiers introduced are useful for measuring uncertainty at pixel level and obtaining reliable area estimates locally. Also some theoretical considerations for the reference sample plotmethod (today named k-NN method in natural resource applications) are presented.

  • 37.
    Stefan, Löfgren
    et al.
    Institutionen för vatten och miljö, SLU.
    Nisell, Jakob
    Institutionen för vatten och miljö, SLU.
    Yu, Jun
    Centre of Biostochastics, SLU.
    Ranneby, Bo
    Centre of Biostochastics, SLU.
    N- och P-halterna i skog, myr och fjäll våren 2011 i Dalälven, Viskan, Ätran, Nissan och Lagan: projekt för att förbättra skattningarna av typhalter inför PLC62011Report (Other academic)
    Abstract [en]

    As part of an earlier pilot project (SMED Report No. 52 2011) and based on data from the national forest survey (RIS) and satellite scenes, the statistical method Probabilistic classifier was used for classifying the forest status of forest land, peat land and mountain areas. Riparian forests were defined based on the virtual streamwater network (VIVAN). Based on data from 200 randomly selected head-waters of the rivers Dalälven, Viskan, Ätran, Nissan and Lagan and the forest sta-tus in riparian and more remote forests, models were created to estimate summer type concentrations of N and P in stream water. The explanation power of the Tot-N and Tot-P models was significantly higher than those used in connection with PLC5 and the modelled type concentrations, representing summer conditions, were significantly higher than those used in PLC5.

    Within this new project, water samples were collected and analyzed in spring 2011 from the 200 randomly selected headwaters of river Dalälven and in western Sweden. The measured summer and spring concentration levels were compared and, based on the same methodology as in the previous pilot project, models were created to estimate the springtime Tot-N and Tot-P type concentrations in stream water. Additionally, water samples were collected in September and November 2011 (in progress), but funding for the chemical analyses are lacking.

    The spring survey showed lower Tot-N and Tot-P concentrations than during the summer inventories, especially in the Dalälven area. At spring, the median values were just over half the summer values. In western Sweden, the differences between seasons were much smaller and based on median values the spring concentrations were 14% and 25% lower for Tot-N and Tot-P, respectively. Compared with the PLC5 type concentrations, the spring values in the Dalälven area were about 35% and 45% lower for Tot-N and Tot-P, respectively, while on the West Coast they were 24-51% higher for Tot-N and 62% higher for Tot-P. Similarly to the summer survey, the spring inventory indicates that the PLC5 type concentrations underes-timated forest leaching of both Tot-N and Tot-P in Western Sweden, while the results from the Dalälven area instead indicates an overestimate. Type concentra-tions produced by models with data only from spring and summer cannot be uncrit-ically used for source apportionment modelling and as a basis for estimating N and P retention from the headwaters to the sea. This requires models based on water chemical data from all seasons.

    The spring survey also showed that the explanation power of the models is signifi-cantly higher than for those used in PLC5, suggesting that there are relations between catchment characteristics and N and P concentrations and that Probabilistic classifier is a useful method for estimating these properties. During both summer and spring, the models explained approximately 60% and 31% of the variation for Tot-N and Tot-P, respectively. The models indicate that the nutrient losses are controlled primarily by the amount of biomass in spring, while growth is ruling during summer.

    Given the typically high water discharge in spring and autumn and the resulting impact on the nutrient transport calculations (= concentration x discharge), there are good reasons to take into account the spatial concentration variations during fall in the PLC6 source apportionments by improving the N and P type concentrations estimates. The chemical analysis of the project collected autumn samples should therefore be funded. In addition, similar surveys should be conducted in northern Sweden in order to improve the estimates of N and P losses from forest land, peat land and mountain areas also in this part of the country.

  • 38.
    Söderström, Tor
    et al.
    Umeå University, Faculty of Social Sciences, Department of Education.
    Fahlén, Josef
    Umeå University, Faculty of Social Sciences, Department of Education.
    Ferry, Magnus
    Umeå University, Faculty of Social Sciences, Department of Education.
    Yu, J
    Umeå University, Faculty of Science and Technology, Department of Science and Mathematics Education.
    Participation in non-elite sport in early adulthood: the impact of athletic ability in childhood and adolescence2015In: 20 th annual Congress of the European college of Sport Science, (ECSS), 24th - 27th June 2015, Malmö – Sweden: book of abstracts / [ed] Radmann, A., Hedenborg, S., Tsolakidis, E., 2015, p. 294-Conference paper (Other academic)
    Abstract [en]

    Introduction Understandings of, explanations to, and predictors of adult participation in organized sport, on the one hand, and expert performances in organized sport as adults on the other hand have received a lot of attention as separate entities by scholars in the areas of sport participation and sport expertise alike. Although scholars in both fields share an interest in tracing explanatory factors and predictors, it is evident that sport participation research has not investigated the impact of factors that are in focus in sport expertise research and vice versa. Thus, in this paper we aim to explore relationships between sport performance during childhood and adolescence and participation in sport in adulthood.

    Methods Data were derived from Web-based questionnaires completed by university students between 2005 and 2012. In total, 572 students (290 men and 282 women) completed the questionnaires. These students were at the beginning of their studies in sports science (n=357) and physical education teacher education (n=215). The questionnaire gathered information about the following topics: • Biographical data: date of birth; • Sport debut: age they started to participate in organized club sports; • Sport performance: self-estimated sporting skills and participation in regional talent groups during childhood and adolescence. • Sport involvement: previous and present involvement in organized club sports;

    Results Results from questionnaires reveal that early sport debut and date of birth positively correlate to strong sport performances during childhood and being selected for talent groups. These variables, in turn, are positively correlated to strong sport performances during adolescence and being selected for talent groups. Strong sport performances during adolescence do not correlate to expert performance as adults. However, strong sport performances during adolescence are positively correlated to sports club membership as adults.

    Discussion These results suggest a need to further explore how factors found to be important for elite sport practice and expert performance, also influence non-elite sport participation in adulthood. Our findings suggest that talent development system selecting children and youth to develop their abilities and to become elite athletes, not only develops potential elite athletes but also shapes the larger recruitment of adults to sport at non-elite levels and participation in general exercise activities.

  • 39.
    Söderström, Tor
    et al.
    Umeå University, Faculty of Social Sciences, Department of Education.
    Fahlén, Josef
    Umeå University, Faculty of Social Sciences, Department of Education.
    Ferry, Magnus
    Umeå University, Faculty of Social Sciences, Department of Education.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Athletic ability in childhood and adolescence as a predictor of participation in non-elite sports in young adulthood2017In: Sport in Society: Cultures, Media, Politics, Commerce, ISSN 1743-0437, E-ISSN 1743-0445, p. 1-18Article in journal (Refereed)
    Abstract [en]

    In this article, we contribute to the discussion on factors affecting adult participation in organized sport. To this end, we examine whether explanations regarding sport expertise can also add to the understanding of non-elite-level sport participation in young adulthood. Results from questionnaires (n = 572) revealed that date of birth and early sport debut positively correlated to strong sport performance during childhood, which, in turn, were correlated to strong sport performance and being selected for talent groups during adolescence. Finally, strong sport performance during adolescence was positively correlated to sports club membership as young adults. As relative age effects seem to remain throughout childhood and adolescence, we conclude that the underlying variable that affects the selection process and sport participation in young adulthood is date of birth. The results indicate that being active in sport as young adults is contingent on sport-specific variables previously not investigated in research on sport participation.

  • 40.
    Teterukovskiy, Alex
    et al.
    SLU, Centre of Biostochastics.
    Yu, Jun
    SLU, Centre of Biostochastics.
    Contextual reclassification of multispectral images: a Markov Random Field approach2002In: Information Processes, ISSN 1819-5822, Vol. 2, no 1, p. 12-21Article in journal (Refereed)
    Abstract [en]

    This work presents methods for multispectral image classification using the contextual classifiersbased on Markov Random Field (MRF) models. Performance of some conventional classification methods is evaluated, through a Monte Carlo study, with or without using the contextual reclassification. Spatial autocorrelation is present in the computer-generated data on a true scene. The total misclassification rates for varying strengths of autocorrelation and for different methods are compared. The results indicate that the combination of the spectral-contextual classifiers can improve to a great extent the accuracyof conventional non-contextual classification methods. It is also shown how the most complicated cases can be handled by the Gibbs sampler.

  • 41.
    Wang, Jianfeng
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Brynolfsson, Patrik
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Liu, Xijia
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Contrast agent quantification by using spatial information in dynamic contrast enhanced MRI2016Manuscript (preprint) (Other academic)
    Abstract [en]

    The purpose of this study is to investigate a method, using simulations, toimprove contrast agent quantication in Dynamic Contrast Enhanced MRI.Bayesian hierarchical models (BHMs) are applied to smaller images such that spatial information can be incorporated. Then exploratory analysisis done for larger images by using maximum a posteriori (MAP).

    For smaller images: the estimators of proposed BHMs show improvementsin terms of the root mean squared error compared to the estimators in existingmethod for a noise level equivalent of a 12-channel head coil at 3T. Moreover,Leroux model outperforms Besag models. For larger images: MAP estimatorsalso show improvements by assigning Leroux prior.

  • 42.
    wang, jianfeng
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Brynolfsson, Patrik
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Liu, Xijia
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Contrast Agent Quantification by Using Spatial Information in Dynamic Contrast Enhanced MRIManuscript (preprint) (Other academic)
  • 43.
    Wang, Jianfeng
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Brynolfsson, Patrik
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Combining phase and magnitude information for contrast agent quantification in dynamic contrast-enhanced MRI using Bayesian hierarchical model2016In: Proceedings of the 8th International Workshop on Spatio-Temporal Modelling, 2016, p. 217-217Conference paper (Other academic)
  • 44.
    Wang, Jianfeng
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Sparsity Estimation of MR images in Compressive Sensing2017Conference paper (Other academic)
  • 45.
    Wang, Jianfeng
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Zhou, Zhiyong
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Sparsity estimation in compressive sensing with application to MR images2017Manuscript (preprint) (Other academic)
    Abstract [en]

    The theory of compressive sensing (CS) asserts that an unknown signal x in C^N canbe accurately recovered from m measurements with m << N provided that x is sparse. Most of the recovery algorithms need the sparsity s = ||x||_0 as an input. However,generally s is unknown, and directly estimating the sparsity has been an open problem.In this study, an estimator of sparsity is proposed by using Bayesian hierarchical model. Its statistical properties such as unbiasedness and asymptotic normality are proved. Inthe simulation study and real data study, magnetic resonance image data is used asinput signal, which becomes sparse after sparsified transformation. The results fromthe simulation study confirm the theoretical properties of the estimator. In practice, theestimate from a real MR image can be used for recovering future MR images under theframework of CS if they are believed to have the same sparsity level after sparsification.

  • 46.
    Wieloch, Thomas
    et al.
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Ehlers, Ina
    Frank, David
    Gessler, Arthur
    Grabner, Michael
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Schleucher, Jürgen
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Tree-ring cellulose exhibits several distinct intramolecular 13C signals2017In: Geophysical Research Abstracts, 2017, Vol. 19, article id EGU2017-14723Conference paper (Refereed)
  • 47.
    Wieloch, Thomas
    et al.
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Ehlers, Ina
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Frank, David
    Grabner, Michael
    Gessler, Arthur
    Schleucher, Jürgen
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Intramolecular 13C analysis of tree rings provides multiple plant ecophysiology signals covering decades2018In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 8, article id 5048Article in journal (Refereed)
    Abstract [en]

    Measurements of carbon isotope contents of plant organic matter provide important information in diverse fields such as plant breeding, ecophysiology, biogeochemistry and paleoclimatology. They are currently based on 13C/12C ratios of specific, whole metabolites, but we show here that intramolecular ratios provide higher resolution information. In the glucose units of tree-ring cellulose of 12 tree species, we detected large differences in 13C/12C ratios (>10‰) among carbon atoms, which provide isotopically distinct inputs to major global C pools, including wood and soil organic matter. Thus, considering position-specific differences can improve characterisation of soil-to-atmosphere carbon fluxes and soil metabolism. In a Pinus nigra tree-ring archive formed from 1961 to 1995, we found novel 13C signals, and show that intramolecular analysis enables more comprehensive and precise signal extraction from tree rings, and thus higher resolution reconstruction of plants’ responses to climate change. Moreover, we propose an ecophysiological mechanism for the introduction of a 13C signal, which links an environmental shift to the triggered metabolic shift and its intramolecular 13C signature. In conclusion, intramolecular 13C analyses can provide valuable new information about long-term metabolic dynamics for numerous applications.

  • 48.
    Wieloch, Thomas
    et al.
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Ehlers, Ina
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Frank, David
    Grabner, Michael
    Gessler, Arthur
    Schleucher, Jürgen
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Tree-ring cellulose exhibits several interannual 13C signals on the intramolecular level2018In: Geophysical Research Abstracts, 2018, Vol. 20, article id EGU2018-17509-2Conference paper (Refereed)
    Abstract
  • 49.
    Xie, Yingfu
    et al.
    SLU, Centre of Biostochastics.
    Yu, Jun
    SLU, Centre of Biostochastics.
    Asymptotics for Quasi-Maximum Likelihood Estimators of GARCH(1,2) Model Under Dependent Innovations2003Report (Other academic)
    Abstract [en]

    In this paper, we investigate the asymptotic properties of the quasi-maximum likelihood estimator (quasi-MLE) for GARCH(1,2) model under stationary innovations. Consistency of the global quasi-MLE and asymptotic normality of the local quasi-MLE are obtained, which extend the previous results for GARCH(1,1) under weaker conditions.

  • 50.
    Xie, Yingfu
    et al.
    SLU, Centre of Biostochastics.
    Yu, Jun
    SLU, Centre of Biostochastics.
    Consistency of Maximum Likelihood Estimators for the Reduced Regime-Switching GARCH Model2005Report (Other academic)
    Abstract [en]

    The regime-switching GARCH model combines the idea of Markov switching and GARCH model, which also extends Hidden Markov models. The statistical inference for this model, however, is rather difficult because the observations depend on the whole regime history. In this paper, we consider a reduced regime-switching GARCH model, that is, the past regimes are integrated out at every step and observations then depend only on the current regimes. We prove the consistency of maximum likelihood estimators for this model. Simulation studies to illustrate consistency, asymptotic normality of the proposed estimators and a model specification problem are also presented.

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