Academy & Industry Research Collaboration Center (AIRCC)

Volume 9, Number 4, March 2019

A Comparison of Active Contour Prior Shape Segmentation Methods: Application to
Diabetic Plantar Foot Thermal Images

  Authors

Asma Bougrine, Rachid Harba, Raphael Canals, Roger Ledee, Meryem Jabloun, PRISME Laboratory - University of Orleans – France

  Abstract

The segmentation of diabetic plantar foot thermal images that are taken with no constraining setup is a challenging problem. The present paper is dedicated to the comparison of three active contour-based methods with prior shape information that are well suited to the given problem. The first method was recently proposed by the present authors. It is based on the Kass et al. method and on a new extra term that minimizes the difference between the curve curvature of the active contour and the prior shape one. The second method is the Ahmed et al. one, a Fourier-based method with prior shape matching. The third one was suggested by Chen et al. where a geodesic snake is associated with a prior shape energy function. Using a database of 50 plantar foot thermal images, results show that our proposed method outperforms the two others with a root-mean-square error (RMSE) equal to 5.12 pixels and a Dice Similarity Coefficient (DSC) score of 93.9%. In addition, our method is robust to initial contour variations and fast, therefore suitable for smartphone application in the context of diabetic foot problem.

  Keywords

Prior shape-based segmentation, active contours, plantar foot thermal images, diabetic foot