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Abstract #1697

Improved Quantitative Spatial Analysis of Spontaneous Muscular Activities using Label Uncertainty and Feature Analysis

Martin Schwartz1,2, Petros Martirosian1, Günter Steidle1, Bin Yang2, and Fritz Schick1
1Section on Experimental Radiology, University Hospital of Tübingen, Tübingen, Germany, 2Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany

Synopsis

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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Keywords