Automatic quantification of muscle volumes in magnetic resonance imaging scans of the lower extremities

Gerd Brunner, Vijay Nambi, Eric Yang, Anirudh Kumar, Salim S. Virani, Panagiotis Kougias, Dipan Shah, Alan Lumsden, Christie M. Ballantyne, Joel D. Morrisett

Research output: Contribution to journalArticle

16 Scopus citations

Abstract

Muscle volume measurements are essential for an array of diseases ranging from peripheral arterial disease, muscular dystrophies, neurological conditions to sport injuries and aging. In the clinical setting, muscle volume is not routinely measured due to the lack of standardized ways for its repeatable quantification. In this paper, we present magnetic resonance muscle quantification (MRMQ), a method for the automatic quantification of thigh muscle volume in magnetic resonance imaging (MRI) scans. MRMQ integrates a thigh segmentation and nonuniform image gradient correction step, followed by feature extraction and classification. The classification step leverages prior probabilities, introducing prior knowledge to a maximum a posteriori classifier. MRMQ was validated on 344 slices taken from 60 MRI scans. Experiments for the fully automatic detection of muscle volume in MRI scans demonstrated an averaged accuracy, sensitivity and specificity for leave-one-out cross-validation of 88.3%, 93.6% and 87.2%, respectively.

Original languageEnglish (US)
Pages (from-to)1065-1075
Number of pages11
JournalMagnetic Resonance Imaging
Volume29
Issue number8
DOIs
Publication statusPublished - Oct 1 2011

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All Science Journal Classification (ASJC) codes

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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