Introduction:

The 3 to 5% of Cuban diabetic patients suffer from diabetic foot ulcer. The diabetic foot ulcer photographic images allow quantitative evaluations of a treatment. In Cuba, the ulcer area measurement is done manually or semi-automatically. There is no Cuban software reported that automatically measures the area, and allows knowing the state of the foot ulcer before and after a treatment.

Goal:

To compare qualitatively (given the absence of a gold standard) ulcer´s pre-processing and segmentation methods.

Method:

We develop a descriptive and transversal study with 6 diabetic patients from Nacional Institute of Angiology and Vascular Surgery during October, 2018, with lesions of degree I-IV in the Wagner scale. The stereotaxic frame FrameHeber03® was used for obtaining planimetric images of the ulcers. In all, 51 ulcer images were obtained, and then we pre-processed it by Logarithmic Discrete Wavelet Transform under a S-LIP model, and found the ulcer border with the segmentation methods Chan-Vese, Gaussian Mixture Model (GMM), and GrabCut.

Results:

The pre-processing step was crutial for obtaining good results in the segmentation step. The best performance was reached by the GMM segmentation method. The algorithms were more accurate in images with black skin patients, due to the high contrast between the skin and the ulcer border.

Conclusions:

The automatic segmentation method (GMM) could be included in a software for detecting the border of the diabetic foot ulcer.

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