A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis

Stefano Cerri*, Andrew Hoopes, Douglas N. Greve, Mark Mühlau, Koen Van Leemput

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

In this paper we propose a novel method for the segmentation of longitudinal brain MRI scans of patients suffering from Multiple Sclerosis. The method builds upon an existing cross-sectional method for simultaneous whole-brain and lesion segmentation, introducing subjectspecific latent variables to encourage temporal consistency between longitudinal scans. It is very generally applicable, as it does not make any prior assumptions on the scanner, the MRI protocol, or the number and timing of longitudinal follow-up scans. Preliminary experiments on three longitudinal datasets indicate that the proposed method produces more reliable segmentations and detects disease effects better than the crosssectional method it is based upon.
Original languageEnglish
Title of host publicationMachine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology : Third International Workshop, MLCN 2020, and Second International Workshop, RNO-AI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings
Volume12449
PublisherSpringer
Publication date2020
Pages119-128
ISBN (Print)978-3-030-66842-6
ISBN (Electronic)978-3-030-66843-3
DOIs
Publication statusPublished - 2020
SeriesLecture Notes in Computer Science
Volume12449
ISSN0302-9743

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