Enhanced deep learning model enables accurate alignment measurement across diverse institutional imaging protocols.

Background: Achieving consistent accuracy in radiographic measurements across different equipment and protocols is challenging. This study evaluates an advanced deep learning (DL) model, building upon a precursor, for its proficiency in generating uniform and precise alignment measurements in full-leg radiographs irrespective of institutional imaging differences.

Methods: The enhanced DL model was trained on over 10,000 radiographs.