Classification of vertebral compression fractures (VCF) having osteoporotic
or neoplastic origin is fundamental to the planning of treatment. We developed
a fracture classification system by acquiring quantitative morphologic and bone
density determinants of fracture progression through the use of automated
measurements from longitudinal studies. A total of 250 CT studies were acquired
for the task, each having previously identified VCFs with osteoporosis or
neoplasm. Thirty-six features or each identified VCF were computed and
classified using a committee of support vector machines. Ten-fold cross
validation on 695 identified fractured vertebrae showed classification
accuracies of 0.812, 0.665, and 0.820 for the measured, longitudinal, and
combined feature sets respectively.Comment: Contributed 4-Page Paper to be presented at the 2016 IEEE
International Symposium on Biomedical Imaging (ISBI), April 13-16, 2016,
Prague, Czech Republi