Application of deep learning algorithm to detect and visualize vertebral fractures on plain frontal radiographs

HSUAN-YU CHENHsu, Benny Wei-YunBenny Wei-YunHsuYin, Yu-KaiYu-KaiYinLin, Feng-HueiFeng-HueiLinYang, Tsung-HanTsung-HanYangRONG-SEN YANGCHIH-KUO LEEFENG-HUEI LIN2021-03-042021-03-0420211932-6203https://scholars.lib.ntu.edu.tw/handle/123456789/550797Identification of vertebral fractures (VFs) is critical for effective secondary fracture prevention owing to their association with the increasing risks of future fractures. Plain abdominal frontal radiographs (PARs) are a common investigation method performed for a variety of clinical indications and provide an ideal platform for the opportunistic identification of VF. This study uses a deep convolutional neural network (DCNN) to identify the feasibility for the screening, detection, and localization of VFs using PARs.animation[SDGs]SDG3Application of deep learning algorithm to detect and visualize vertebral fractures on plain frontal radiographsjournal article10.1371/journal.pone.0245992335079822-s2.0-85100296244