Hui-Zhao Wu, Li-Feng Yan, Xiao-Qing Liu, Yi-Zhou Yu, Zuo-Jun Geng, Wen-Juan Wu, Chun-Qing Han, Yong-Qin Guo, Bu-Lang Gao
This study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, to mitigate feature ambiguity in bone fracture detection on radiographs of various body parts. A total of 9040 radiographic studies were extracted. These images were classified into several body part types including 1651 hand, 1302 wrist, 406 elbow, 696 shoulder, 1580 pelvic, 948 knee, 1180 ankle, and 1277 foot images. Instance segmentation was annotated by radiologists. The ResNext-101+FPN was employed as the baseline network structure and the FAMO model for processing...
January 15, 2021: Scientific Reports