Automatic Wound Assessment Using 2D Photos and Mapping onto Patient-specific 3D Models

Automatically mapping wounds from a 2D diagnostic photo onto a 3D morphable model benefits the treatment of acute burn wounds and the documentation of chronic wounds in that it makes the annotation process faster and reduces human error. We propose a pipeline comprising patient shape estimation, wound segmentation, and 2D to 3D location mapping based on deep learning (DL) techniques that facilitates automatic wound transfer from 2D photos onto 3D models.