Enhanced diagnosis of pes planus and pes cavus using deep learning-based segmentation of weight-bearing lateral foot radiographs: a comparative observer study.

ABSTRACT: A weight-bearing lateral radiograph (WBLR) of the foot is a gold standard for diagnosing adult-acquired flatfoot deformity. However, it is difficult to measure the major axis of bones in WBLR without using auxiliary lines. Herein, we develop semantic segmentation with a deep learning model (DLm) on the WBLR of the foot for enhanced diagnosis of pes planus and pes cavus. We used 300 consecutive WBLRs from young Korean males. The semantic segmentation model was developed based on U²-Net. An expert orthopedic surgeon manually labeled ground truths. We used 200 radiographs for training, 100 for internal validation, and two external datasets for external validation. The model was trained using a hybrid loss function, combining Dice Loss and boundary-based loss, to enhance both overal

SUBMITTER: Ryu SM 

PROVIDER: S-EPMC11704119 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature