Accurate Chronic Wound Area Measurement using Structure from Motion
Chronic Wounds, Computer Vision, 3D Reconstruction, Surface Area, Structure from Motion.
Chronic wounds are ulcers that have a difficult or almost interrupted healing process,
leading to an increased risk of health complications, such as amputations and changes. The
need for quantitative areas is of great importance in clinical trials, pathological analysis of
wounds and daily patient care. Manual and 2D manuals cannot solve the problems caused
by the curvatures of the human body and different camera angles. This work proposes
the use of a non-invasive methodology to perform 3D reconstruction of the human body
surface to measure wound areas, which combines a combined image, Structure from Motion
(SfM) with different descriptors, SIFT, SURF, ORB and BRIEF and mesh reconstruction
to obtain a reliable representation of the skin surface. The results show that accurate
measurements of 3D surface areas can be obtained from images acquired with a smartphone
using the proposed methodology, with average errors of 1.7% for SIFT, 3.6% for SURF,
6.4% for ORB and 20.8% for BRIEF, using a configuration of 10 images, while the average
error for 2D occurrences was 32.7%, clearly pointing to the superiority of the 3D method.