Classification of Breast Lesions in Frontal Thermographic Images Using a Diagnosis Aid Intelligent System-Reference-Cited by-同舟云学术

Classification of Breast Lesions in Frontal Thermographic Images Using a Diagnosis Aid Intelligent System

Published:2022-07-01 Issue: Volume: Page:76-95
ISSN:
Container-title:Research Anthology on Medical Informatics in Breast and Cervical Cancer
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Author:

Araújo de Santana Maíra¹^ORCID,Pereira Jessiane Mônica Silva¹,Lins de Lima Clarisse¹,Jacinto de Almeida Maria Beatriz¹,Silva de Andrade José Filipe¹,Silva de Souza Thifany Ketuli¹,Fernandes de Lima Rita de Cássia¹,Pinheiro dos Santos Wellington¹^ORCID

Affiliation:

1. Universidade Federal de Pernambuco, Brazil

Abstract

This study aims to assess the breast lesions classification in thermographic images using different configuration of an Extreme Learning Machine network as classifier. In this approach, the authors changed the number of neurons in the hidden layer and the type of kernel function to further explore the network in order to find a better solution for the classification problem. Authors also used different tools to perform features extraction to assess both texture and geometry information from the breast lesions. During the study, the authors found that the results changed not only due to the network parameters but also due to the features chosen to represent the thermographic images. A maximum accuracy of 95% was found for the differentiation of breast lesions.

Publisher

IGI Global

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