Compression Fractures Detection on CT
June 06, 2017 Β· Declared Dead Β· π Medical Imaging
"No code URL or promise found in abstract"
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Authors
Amir Bar, Lior Wolf, Orna Bergman Amitai, Eyal Toledano, Eldad Elnekave
arXiv ID
1706.01671
Category
cs.CV: Computer Vision
Citations
68
Venue
Medical Imaging
Last Checked
5 months ago
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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