Anette Karlsson1,
2, Johannes Rosander3, Joakim Tallberg2, Thobias
Romu1, 2, Magnus Borga1, 2, Olof
Dahlqvist Leinhard, 24
1Department
of Biomedical Engineering (IMT), Linkping University, Linkping, Sweden; 2Center
for Medical Image Science and Visualization (CMIV), Linkping University,
Linkping, Sweden; 3Advanced MR Analytics (AMRA) AB, Linkping,
Sweden; 4Department of Medical and Health Sciences (IMH),
Linkping University, Linkping, Sweden
Fat and water separated MRI enables non-invasive quantification of volume and fat infiltration in muscles. Manual segmentation of muscles is extremely time consuming why automatic alternatives are needed. . We have developed an infrastructure that enables a robust platform for non-rigid whole body registration where manual classifications of an anatomical structure in an image volume (prototype) may be automatically transferred to a new patient volume. The purpose of this work was to evaluate if using such multiple prototype voting procedure provides a robust automatic muscle classification. The result showed satisfying robustness in all 10 subjects using multiple prototype voting.
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