Polytechnic University of Valencia Congress, INNODOCT 2019

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Analysis of segmentation methods for acne vulgaris images. Proposal of a new methodology applied to fluorescence images
María Moncho Santonja, María Begoña Sanz Alamán, Beatriz Defez García, Ismael Lengua Lengua, Guillermo Peris-Fajarnés

Last modified: 10-04-2020

Abstract


Acne vulgaris is one of the most common human pathologies worldwide. Its prevalence causes a high healthcare expenditure. Acne healthcare costs and effects on individuals' quality of life lead to the need of analysing current acne evaluation, treatment and monitoring methods. One of the most common ones is manual lesion counting by a dermatologist. However, this technique has several limitations, such as time spent. That is the reason why the development of new computer-assisted techniques are needed in order to automatically count the acne lesions. Nonetheless, the first step is automatic acne lesion detection on the skin of patients. The aim of this work is to propose a new methodology to solve the acne images segmentation problem, so that the implementation of a system for automatic counting is possible. The results would be a decrease in both time spent and diagnosis errors. With this objective, after doing a systematic review on the state of the art of acne images segmentation methods, fluorescence images of the face of acne patients are obtained. This image modality enhances visualization of the acne lesions. Finally, using the fluorescence images, a segmentation algorithm is implemented in MATLAB.

Keywords


image segmentation; acne vulgaris; MATLAB; fluorescence imaging; machine learning; image processing

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