Development and validation of a fully automated tool to quantify 3D foot and ankle alignment using weight-bearing CT.

Introduction: Foot and ankle alignment plays a pivotal role in human gait and posture. Traditional assessment methods, relying on 2D standing radiographs, present limitations in capturing the dynamic 3D nature of foot alignment during weight-bearing and are prone to observer error. This study aims to integrate weight-bearing CT (WBCT) imaging and advanced deep learning (DL) techniques to automate and enhance quantification of the 3D foot and ankle alignment.