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  • 1.
    Garpebring, Anders
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Wirestam, Ronnie
    Östlund, Nils
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Karlsson, Mikael
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Effects of inflow and radiofrequency spoiling on the arterial input function in dynamic contrast-enhanced MRI: a combined phantom and simulation study2011Inngår i: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 65, nr 6, s. 1670-1679Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The arterial input function is crucial in pharmacokinetic analysis of dynamic contrast-enhanced MRI data. Among other artifacts in arterial input function quantification, the blood inflow effect and nonideal radiofrequency spoiling can induce large measurement errors with subsequent reduction of accuracy in the pharmacokinetic parameters. These errors were investigated for a 3D spoiled gradient-echo sequence using a pulsatile flow phantom and a total of 144 typical imaging settings. In the presence of large inflow effects, results showed poor average accuracy and large spread between imaging settings, when the standard spoiled gradient-echo signal equation was used in the analysis. For example, one of the investigated inflow conditions resulted in a mean error of about 40% and a spread, given by the coefficient of variation, of 20% for K(trans) . Minimizing inflow effects by appropriate slice placement, combined with compensation for nonideal radiofrequency spoiling, significantly improved the results, but they remained poorer than without flow (e.g., 3-4 times larger coefficient of variation for K(trans) ). It was concluded that the 3D spoiled gradient-echo sequence is not optimal for accurate arterial input function quantification and that correction for nonideal radiofrequency spoiling in combination with inflow minimizing slice placement should be used to reduce the errors. Magn Reson Med, 2011. © 2011 Wiley-Liss, Inc.

  • 2.
    Garpebring, Anders
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Östlund, Nils
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Karlsson, Mikael
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    A novel estimation method for physiological parameters in dynamic contrast-enhanced MRI: application of a distributed parameter model using Fourier-domain calculations2009Inngår i: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 28, nr 9, s. 1375-1383Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Dynamic contrast-enhanced magnetic resonance imaging (MRI) is a promising tool in the evaluation of tumor physiology. From rapidly acquired images and a model for contrast agent pharmacokinetics, physiological parameters are derived. One pharmacokinetic model, the tissue homogeneity model, enables estimation of both blood flow and vessel permeability together with parameters that describe blood volume and extracellular extravascular volume fraction. However, studies have shown that parameter estimation with this model is unstable. Therefore, several initial guesses are needed for accurate estimates, which makes the estimation slow. In this study a new estimation algorithm for the tissue homogeneity model, based on Fourier domain calculations, was derived and implemented as a Matlab program. The algorithm was tested with Monte-Carlo simulations and the results were compared to an existing method that uses the adiabatic approximation. The algorithm was also tested on data from a metastasis in the brain. The comparison showed that the new algorithm gave more accurate results on the 2.5th and 97.5th percentile levels, for instance the error in blood volume was reduced by 21%. In addition, the time needed for the computations was reduced with a factor 25. It was concluded that the new algorithm can be used to speed up parameter estimation while accuracy can be gained at the same time.

  • 3. Gerdle, Björn
    et al.
    Östlund, Nils
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF). Department of Biomedical Engineering and Informatics, University Hospital, Umeå, Sweden.
    Grönlund, Christer
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF). Department of Biomedical Engineering and Informatics, University Hospital, Umeå, Sweden.
    Roeleveld, Karin
    Karlsson, Stefan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF). Department of Biomedical Engineering and Informatics, University Hospital, Umeå, Sweden.
    Firing rate and conduction velocity of single motor units in the trapezius muscle in fibromyalgia patients and healthy controls2008Inngår i: Journal of Electromyography & Kinesiology, ISSN 1050-6411, E-ISSN 1873-5711, Vol. 18, nr 5, s. 707-716Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Fibromyalgia is a common chronic pain condition in the population (2-4%), which often is associated with prominent negative consequences with respect to participation in daily activities. There are several reports in the literature concerning the effects of acute experimental pain on motor control. However, a more heterogeneous picture exists in the literature with respect to whether chronic pain conditions affect motor control. This study compares firing rate and conduction velocity (CV) of single motor units (MUs) in the trapezius muscle of fibromyalgia patients (FM) and healthy controls (CON). Multi-channel surface electromyography was used to estimate both MU firing rate and CV because this technique allows simultaneous estimation of both these variables and the measurements are easy and non-invasive. In this study, 29 FM and 30 CON subjects participated and performed isometric shoulder elevations using weights up to 4 kg. No significant differences in the firing rate of MUs in the trapezius muscle were found between the FM and CON groups (95% confidence interval was -1.9 and 1.3 pulses per second). There were no significant differences in CV between the groups at 1 and 2 kg load. However, the FM group had significantly higher CV in contractions without external load (p=0.004). We were unable to confirm the pain-adaptation model since no differences in firing rate between the two groups were found. CV was significantly higher in FM than in healthy controls; this might be due to alterations in histopathology and microcirculation.

  • 4.
    Grönlund, Christer
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF). Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Östlund, Nils
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF). Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Lindh, Jack
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Bergström, Per
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Karlsson, Stefan J
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Spatio-temporal processing of surface EMG signals from the sternocleidomastoideus muscle to assess effects of radiotherapy on motor unit conduction velocity and firing rate: a pilot study2008Inngår i: Biomedical Signal Processing and Control, ISSN 1746-8094, Vol. 3, nr 2, s. 163-168Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Radiation therapy causes both muscle and nerve tissue damage. However, the evolution and mechanisms of these damages are not fully understood. Information on the state of active muscle fibres and motoneurons can be obtained by measuring sEMG signals and calculating the conduction velocity (CV) and firing rate of individual motor units, respectively. The aim of this pilot study was to evaluate if the multi-channel surface EMG (sEMG) technique could be applied to the sternocleidomastoideus muscle (SCM) of radiotherapy patients, and to assess if the CV and firing rate are altered as a consequence of the radiation.

    Surface EMG signals were recorded from the radiated and healthy SCM muscles of 10 subjects, while subjects performed isometric rotation of the head. CV and firing rate were calculated using two recently proposed methods based on spatio-temporal processing of the sEMG signals. The multi-channel sEMG technique was successfully applied to the SCM muscle and CV and firing rates were obtained. The measurements were fast and simple and comfortable for the patients. Sufficient data quality was obtained from both sides of seven and four subjects for the CV and firing rate analysis, respectively. No differences in CV or firing rate were found between the radiated and non-radiated sides (p = 0.13 and p = 0.20, respectively). Firing rate and CV were also obtained from a myokymic discharge pattern. It was found that the CV decreased significantly (p = 0.01) during the bursts.

  • 5.
    Grönlund, Christer
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper.
    Östlund, Nils
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper.
    Roeleveld, Karin
    Karlsson, J Stefan
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper.
    Simultaneous estimation of muscle fibre conduction velocity and muscle fibre orientation using 2D multichannel surface electromyogram2005Inngår i: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 43, nr 1, s. 63-70Artikkel i tidsskrift (Fagfellevurdert)
  • 6.
    Häggström, Ida
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Johansson, Lennart
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Larsson, Anne
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Östlund, Nils
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Sörensen, Jens
    Medical Sciences, Nuclear Medicine, Uppsala University Hospital, Uppsala, Sweden.
    Karlsson, Mikael
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Semi-automatic tumour segmentation by selective navigation in a three-parameter volume, obtained by voxel-wise kinetic modelling of 11C-acetate2010Inngår i: Radiation Protection Dosimetry, ISSN 0144-8420, E-ISSN 1742-3406, Vol. 139, nr 1-3, s. 214-218Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Positron emission tomography (PET) is increasingly used for delineation of tumour tissue in, for example, radiotherapy treatment planning. The most common method used is to outline volumes with a certain per cent uptake over background in a static image. However, PET data can also be collected dynamically and analysed by kinetic models, which potentially represent the underlying biology better. In the present study, a three-parameter kinetic model was used for voxel-wise evaluation of (11)C-acetate data of head/neck tumours. These parameters which represent the tumour blood volume, the uptake rate and the clearance rate of the tissue were derived for each voxel using a linear regression method and used for segmentation of active tumour tissue. This feasibility study shows that it is possible to segment images based on derived model parameters. There is, however, room for improvements concerning the PET data acquisition, noise reduction and the kinetic modelling. In conclusion, this early study indicates a strong potential of the method even though no 'true' tumour volume was available for validation.

  • 7.
    Karlsson, J Stefan
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Roeleveld, Karin
    Grönlund, Christer
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Holtermann, Andreas
    Östlund, Nils
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Signal processing of the surface electromyogram to gain insight into neuromuscular physiology.2009Inngår i: Philosophical Transactions. Series A: Mathematical, physical, and engineering science, ISSN 1364-503X, E-ISSN 1471-2962, Vol. 367, nr 1887, s. 337-356Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A surface electromyogram (sEMG) contains information about physiological and morphological characteristics of the active muscle and its neural strategies. Because the electrodes are situated on the skin above the muscle, the sEMG is an easily obtainable source of information. However, different combinations of physiological and morphological characteristics can lead to similar sEMG signals and sEMG recordings contain noise and other artefacts. Therefore, many sEMG signal processing methods have been developed and applied to allow insight into neuromuscular physiology. This paper gives an overview of important advances in the development and applications of sEMG signal processing methods, including spectral estimation, higher order statistics and spatio-temporal processing. These methods provide information about muscle activation dynamics and muscle fatigue, as well as characteristics and control of single motor units (conduction velocity, firing rate, amplitude distribution and synchronization).

  • 8.
    Wiklund, Urban
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Karlsson, Marcus
    Östlund, Nils
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Berglin, Lena
    Lindecrantz, Kaj
    Karlsson, Stefan
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Sandsjö, Leif
    Adaptive spatio-temporal filtering of disturbed ECGs: a multi-channel approach to heartbeat detection in smart clothing.2007Inngår i: Medical and Biological Engineering and Computing, ISSN 0140-0118, Vol. 45, nr 6, s. 515-523Artikkel i tidsskrift (Fagfellevurdert)
  • 9.
    Yu, Jun
    et al.
    SLU, Centre of Biostochastics.
    Östlund, Nils
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF). Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Wavelet based noise reduction of four-dimensional data with application to MRI2012Rapport (Annet vitenskapelig)
    Abstract [en]

    This paper is devoted to the development of noise reduction methods for spatial-temporal signals with applications in magnetic resonance imaging. A noise reduction algorithm for 4D MRI signals, based on thewavelet transform and Gaussian scale mixtures, is proposed here. Simulation study shows that the new method is capable to improve theperformance of noise reduction in higher dimensions.

  • 10.
    Yu, Jun
    et al.
    Biostokastikum, SLU.
    Östlund, Nils
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF). Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Löthgren, Pia
    Biostokastikum, SLU.
    Wavelet based noise reduction and parameter estimation in magnetic resonance signals2010Konferansepaper (Fagfellevurdert)
  • 11. Östlund, Nils
    et al.
    Suhr, Ole B
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin.
    Wiklund, Urban
    Wavelet Coherence Detects Non-autonomic Heart Rate Fluctuations in Familial Amyloidotic Polyneuropathy2007Inngår i: 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, ISSN 1557-170X, Vol. 1, s. 4660-4662Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Heart rate variability (HRV) is often used to study disturbances in the autonomic nervous system. Respiratory related HRV is seen as an indicator of a working autonomic mechanism. However, sometimes a high HRV may be caused by non-autonomic mechanisms. This study investigated if the wavelet coherence could be used to study respiratory related fluctuations in heart rate. The wavelet coherence method was applied to two Familial amyloidotic polyneuropathy patients and one healthy control. The results showed that wavelet coherence is a promising method for studying respiratory related fluctuations in heart rate.

  • 12.
    Östlund, Nils
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF).
    Wiklund, Urban
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF).
    Yu, Jun
    Centre of Biostochastics, SLU.
    Karlsson, Stefan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Centrum för medicinsk teknik och fysik (CMTF).
    Adaptive spatio-temporal filtration of bioelectrical signals2005Inngår i: Proceedings of The 27th Annual International Conferenceof the IEEE Engineering in Medicine and Biology Society, New York: IEEE Press, 2005, s. 5983-5986Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper we show how independent component analysis (ICA) algorithms can be used to perform spatio-temporal filtration of electromyographic (EMG) and electrocardiographic (ECG) signals. The technique was used to decompose the EMG signals into motor unit action potential (MUAP) trains. From the 88 outputs of the adaptive spatio-temporal filtration, three groups of different MUAP train patterns were found. The technique was also used to obtain a fetus' ECG and showed better result compared to using ICA.

  • 13.
    Östlund, Nils
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Yu, Jun
    SLU, Centre of Biostochastics.
    Karlsson, Stefan
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Radiofysik.
    Adaptive spatio-temporal filtering of multichannel surface EMG signals2006Inngår i: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 44, nr 3, s. 209-215Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A motor unit (MU) is defined as an anterior horn cell, its axon, and the muscle fibres innervated by the motor neuron. A surface electromyogram (EMG) is a superposition of many different MU action potentials (MUAPs) generated by active MUs. The objectives of this study were to introduce a new adaptive spatio-temporal filter, here called maximum kurtosis filter (MKF), and to compare it with existing filters, on its performance to detect a single MUAP train from multichannel surface EMG signals. The MKF adaptively chooses the filter coefficients by maximising the kurtosis of the output. The proposed method was compared with five commonly used spatial filters, the weighted low-pass differential filter (WLPD) and the marginal distribution of a continuous wavelet transform. The performance was evaluated using simulated EMG signals. In addition, results from a multichannel surface EMG measurement fro from a subject who had been previously exposed to radiation due to cancer were used to demonstrate an application of the method. With five time lags of the MKF, the sensitivity was 98.7% and the highest sensitivity of the traditional filters was 86.8%, which was obtained with the WLPD. The positive predictivities of these filters were 87.4 and 80.4%, respectively. Results from simulations showed that the proposed spatio-temporal filtration technique significantly improved performance as compared with existing filters, and the sensitivity and the positive predictivity increased with an increase in number of time lags in the filter.

1 - 13 of 13
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