Hough Transform Sensitivity Factor Calculation Model Applied to the Analysis of Acne Vulgaris Skin Lesions

María Moncho Santonja,Bàrbara Micó-Vicent,Beatriz Defez,Guillermo Peris-Fajarnes,Jorge Jordán

doi:10.3390/app12031691

María Moncho Santonja, Bàrbara Micó-Vicent + Show 3 more

Open Access

https://doi.org/10.3390/app12031691

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Abstract

The number of infectious spots or pathological structures recorded on dermatological images is a tool to aid in the diagnosis and monitoring of disease progression. Dermatological images for the detection and monitoring of the evolution of acne infections are evaluated globally, comparing whether the increase or decrease in infectious lesions appearing on an image is significant. This evaluation method is only indicative since its accuracy is low. The accuracy problem could be improved by an exact count of the number of structures and spots appearing on the image. The mathematical function circular Hough transform (CHT) function implemented in MATLAB is here applied to develop a procedure for counting these structures. CHT has been used in the recognition of benign and distorted red blood cells, in the detection of pellet sizes in industrial processes and in the automated detection and morphological characterization of breast tumor masses from infrared images, as well as for the detection of brain aneurysms and use in magnetic resonance imaging. The sensitivity factor is one of the many parameters required to feed the CHT algorithm. Its choice is unclear as there is no proper methodology to select an optimum value suitable for each image. In this work, a procedure for determining the optimal value of the sensitivity factor is proposed The approach is validated by comparison with the results of the manual counting of the points (ground truth).

Highlights

To date, there is no standardized way of monitoring the evolution of the pathology caused by acne vulgaris infection
We obtain an algorithm that provides us with the optimal sensitivity factor for counting the number of infected points that appear in fluorescence images processed with the circular Hough transform (CHT) function
CHT is implemented in the MATLAB software, ToolBox Image Segmenter in the function imfindcircles so that the parameters to be entered are the minimum and maximum diameter of the circular objects to be identified and a sensitivity factor, among others

Summary

Introduction

There is no standardized way of monitoring the evolution of the pathology caused by acne vulgaris infection. The circular Hough transform function (CHT) is one of the most robust spot detection and counting algorithms available, but for its correct implementation it is necessary to choose a sensitivity factor, which until now has been chosen randomly or empirically. An automated way of choosing the optimal sensitivity factor for the algorithm and for each image to be processed is developed. We obtain an algorithm that provides us with the optimal sensitivity factor for counting the number of infected points that appear in fluorescence images processed with the CHT function. The implementation of the Hough transform function in MATLAB had as a weak point the choice of the optimal sensitivity factor This problem is solved in the present work and will allow the algorithm to be applied accurately by the entire scientific community. An algorithm for choosing the optimal sensitivity factor is proposed

Background

CHT in Matlab

Material and Methods

Findings

Conclusions