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Quantification of white matter lesions on brain MRI with 2D fuzzy weighted recurrence networks
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. (Pattern Recognition)ORCID iD: 0000-0002-4255-5130
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

White matter lesions detected on magnetic resonance imaging scans of the brain have been hypothesized to have associations with the causes of several diseases. Accurate quantification of white matter lesions is important for the hypothesis validation. However, the clinical quantification is highly variable due to subjective opinions of different raters and is likely to compromise the reliability of the assessment. This paper introduces a new method of two-dimensional fuzzy weighted recurrence networks that can numerically express the quantity of white matter lesions. The results illustrate the promising application of the proposed method that offers as a useful computational tool in brain research.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019. p. 110-113
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-157173DOI: 10.1109/NER.2019.8717150ISI: 000469933200028ISBN: 9781538679210 (electronic)ISBN: 9781538679227 (print)OAI: oai:DiVA.org:liu-157173DiVA, id: diva2:1319452
Conference
9th International IEEE/EMBS Conference on Neural Engineering (NER'19), San Francisco, CA, USA, 20-23 March 2019
Available from: 2019-06-01 Created: 2019-06-01 Last updated: 2019-07-03Bibliographically approved

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Pham, Tuan

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Citation style
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  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
  • rtf