Keywords: Muscle, Muscle
Motivation: Understanding the visual representation of spontaneous activities in DWI.
Goal(s): Automatically identifying visual differences in patterns of spontaneous muscular activities.
Approach: Deep-learning based detection and segmentation with subsequent feature analysis.
Results: Feasibility of feature-based clustering in individual subjects was shown.
Impact: Investigation of a pipeline for automated image processing for exploring differences in spontaneous muscular activities visible in DWI.
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