Deep Learning-Based Landmark Detection Model for Multiple Foot Deformity Classification: A Dual-Center Study.

ABSTRACT:

Purpose

To introduce heatmap-in-heatmap (HIH)-based model for automated diagnosis of foot deformities using weight-bearing foot radiographs, aiming to address the labor-intensive and variable nature of manual diagnosis.

Materials and methods

From January 2004 to September 2022, a dual-center retrospective study was conducted. In the first center, 1561 anterior-posterior (AP) and 1536 lateral images from 806 patients were used for model training, while 374 AP and 373 lateral images from 196 patients were allocated to the validation set. For external validation at the second center, 527 AP and 529 lateral images from 270 patients were allocated. Five deformities were diagnosed using four and three angles between the predicted landmarks in the AP and lateral images, respectivel

SUBMITTER: Lee SJ 

PROVIDER: S-EPMC12303672 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature