Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs
Abstract
To identify the feasibility of using a deep convolutional neural network (DCNN) for the detection and localization of hip fractures on plain frontal pelvic radiographs (PXRs). Hip fracture is a leading worldwide health problem for the elderly. A missed diagnosis of hip fracture on radiography leads to a dismal prognosis. The application of a DCNN to PXRs can potentially improve the accuracy and efficiency of hip fracture diagnosis. A DCNN was...
Paper Details
Title
Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs
Published Date
Apr 1, 2019
Journal
Volume
29
Issue
10
Pages
5469 - 5477
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