Automatic Detection of Lupus Butterfly Malar Rash Based on Transfer Learning

Author:

Souza Jhonatan,De Oliveira Tiago,Casa Claudemir,Ortoncelli André

Abstract

This work presents an approach to the automatic detection of Butterfly Malar Rash (BMR) in images. BMR is a Lupus symptom characterized by a reddish facial rash that appears symmetrically in the cheeks and the back of the nose. The proposed approach is based on Transfer Learning, a popular approach in Deep Learning that consists in the use of pre-trained models as the starting point for computer vision and natural language processing tasks. To perform the experiments, a database was created with images manually collected from the Instagram social network, searching for images with #butterflyrash. We evaluated the proposed approach with eight Convolutional Neural Networks (CNN) architecture. The experimental results are good results, with a precision of up to 0.957.

Publisher

Sociedade Brasileira de Computação - SBC

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Butterfly Malar Rash Detection Model for Early Systemic Lupus Erythematosus Diagnosis;2023 26th International Conference on Computer and Information Technology (ICCIT);2023-12-13

2. Computer Vision in Autoimmune Diseases Diagnosis—Current Status and Perspectives;Computational Vision and Bio-Inspired Computing;2022

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