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15 February 2021 A system for fully automated monitoring of lesion evolution over time in multiple sclerosis
Sven Kuckertz, Florian Weiler, Britta Matusche, Carsten Lukas, Lothar Spies, Jan Klein, Stefan Heldmann
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Proceedings Volume 11597, Medical Imaging 2021: Computer-Aided Diagnosis; 115972D (2021) https://doi.org/10.1117/12.2582156
Event: SPIE Medical Imaging, 2021, Online Only
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Abstract
Inflammatory white matter brain lesions are a key pathological finding in patients suffering from multiple sclerosis (MS). Image based quantification of different characteristics of these lesions has become an elemental bio-marker in both diagnosis as well as therapy monitoring during treatment of these patients. Whilst it has been shown that the lesion load at a single point in time is only of limited value with respect to explaining clinical symptoms of the patients, a more robust estimate of disease activity can be observed by analyzing the evolution of lesions over time. Here, we propose a system for automated monitoring of temporal lesion evolution in MS. We describe an approach for analysis of lesion correspondence, along with a pipeline for fully automated computation of this model. The pipeline consists of a U-Net based lesion segmentation, a non-linear image registration between multiple studies, computation of temporal lesion correspondences, and finally an analysis module for extracting and visualizing quantitative parameters from the model.
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Sven Kuckertz, Florian Weiler, Britta Matusche, Carsten Lukas, Lothar Spies, Jan Klein, and Stefan Heldmann "A system for fully automated monitoring of lesion evolution over time in multiple sclerosis", Proc. SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis, 115972D (15 February 2021); https://doi.org/10.1117/12.2582156
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KEYWORDS
Brain
Computing systems
Image registration
Image segmentation
Visual analytics
Visual process modeling
Visualization
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