Segmentation of the Fascia Lata in Magnetic Resonance Images of the Thigh: Comparison of an Unsupervised Technique with a U-Net in 2D and Patch-wise 3D
Lis J. Louise P, Klaus Engelke, Oliver Chaudry
Friedrich-Alexander Universität Erlangen-Nürnberg, Institute of Medical Physics
Abstract
To quantify muscle properties in the thigh, the segmentation of the fascia lata is crucial. For this purpose, the U-Net architecture was implemented and compared for 2D images and patched 3D image stacks in magnetic resonance images (MRI). The training data consisted of T1 MRI data sets from elderly men. To test the performance of the models, they were applied on other data sets of different age groups and gender. The U-Net approaches were superior to an unsupervised semiautomatic method and reduced post-processing time.