Umeå University's logo

umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Convolutional Neural Network for Classification of Gait Disorders from Magnetic Resonance Brain Imaging
Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Science and Technology, Department of Physics.
2020 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Place, publisher, year, edition, pages
2020. , p. 21
Keywords [en]
neural network, deep neural network, magnetic resonance imaging, convolutional neural network, CNN, MRI, MR, INPH, NPH, dense blocks, image classification
National Category
Medical Imaging
Identifiers
URN: urn:nbn:se:umu:diva-167457OAI: oai:DiVA.org:umu-167457DiVA, id: diva2:1390901
Subject / course
Examensarbete i teknisk fysik
Educational program
Master of Science Programme in Engineering Physics
Presentation
2019-11-01, Universitetsklubben, Universums gränd 4, Umeå, 10:00 (English)
Supervisors
Examiners
Available from: 2020-02-05 Created: 2020-02-03 Last updated: 2025-02-09Bibliographically approved

Open Access in DiVA

No full text in DiVA

Search in DiVA

By author/editor
Mogensen, Klara
By organisation
Department of Radiation SciencesDepartment of Physics
Medical Imaging

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 993 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf