Fully automatic system to detect and segment the proximal femur in pelvic radiographic images for Legg–Calvé–Perthes disease
Sofie Ditmer,
Nicole Dwenger,
Louise N. Jensen
et al.
Abstract:This study aimed to develop a method using computer vision techniques to accurately detect and delineate the proximal femur in radiographs of Legg–Calvé–Perthes disease (LCPD) patients. Currently, evaluating femoral head deformity, a crucial predictor of LCPD outcomes, relies on unreliable categorical and qualitative classifications. To address this limitation, we employed the pretrained object detection model YOLOv5 to detect the proximal femur on over 2000 radiographs, including images of shoulders and chest… Show more
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