3 March 2017 Compression fractures detection on CT
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Abstract
The presence of a vertebral compression fracture is highly indicative of osteoporosis and represents the single most robust predictor for development of a second osteoporotic fracture in the spine or elsewhere. Less than one third of vertebral compression fractures are diagnosed clinically. We present an automated method for detecting spine compression fractures in Computed Tomography (CT) scans. The algorithm is composed of three processes. First, the spinal column is segmented and sagittal patches are extracted. The patches are then binary classified using a Convolutional Neural Network (CNN). Finally a Recurrent Neural Network (RNN) is utilized to predict whether a vertebral fracture is present in the series of patches.
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Amir Bar, Amir Bar, Lior Wolf, Lior Wolf, Orna Bergman Amitai, Orna Bergman Amitai, Eyal Toledano, Eyal Toledano, Eldad Elnekave, Eldad Elnekave, } "Compression fractures detection on CT", Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 1013440 (3 March 2017); doi: 10.1117/12.2249635; https://doi.org/10.1117/12.2249635
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