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An image processing strategy for the quantification and visualization of exercise‐induced muscle MRI signal enhancement
Author(s) -
Warfield Simon K.,
Mulkern Robert V.,
Winalski Carl S.,
Jolesz Ferenc A.,
Kikinis Ron
Publication year - 2000
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/(sici)1522-2586(200005)11:5<525::aid-jmri8>3.0.co;2-2
Subject(s) - visualization , computer science , image processing , segmentation , skeletal muscle , signal (programming language) , biomedical engineering , computer vision , artificial intelligence , medicine , image (mathematics) , anatomy , programming language
Exercise increases the skeletal muscle water signal in T2‐weighted images. Potential medical applications of MR studies of exercise‐induced muscle signal intensity changes are the assessment of myopathies, sport training regimens, and physical therapy approaches following surgeries. We developed an automated image processing technique that provides volumetric analysis and visualization of exercise‐related T2‐weighted image intensity changes. The image processing was applied to the segmentation and quantification of activated muscle volumes. Qualitative assessment of muscle activation is demonstrated with three‐dimensional surface rendering. Quantitative determination of active muscle volume, signal intensity, and change over time is demonstrated. Visualization of the activated muscles allows functional anatomical assessment of exercise, which in turn allows detection of muscle utilization. J. Magn. Reson. Imaging 2000;11:525–531. © 2000 Wiley‐Liss, Inc.