Segmentação de Pólipos em Imagens de Colonoscopia utilizando YOLOv8

• Sandro Luis de Araujo Junior UTFPR
• Michel Hanzen Scheeren UTFPR
• Rubens Miguel Gomes Aguiar CEIA
• Eduardo Mendes UTFPR
• Ricardo Augusto Pereira Franco UFG
• Pedro Luiz de Paula Filho UTFPR

DOI: https://doi.org/10.5753/sbcas.2024.2180

Resumo

A segmentação de pólipos em imagens de colonoscopia é uma importante tarefa de diagnóstico auxiliado por computador, uma vez que pode auxiliar médicos na identificação e consequentemente remoção dos pólipos, contribuindo assim para a redução dos casos de câncer colorretal, um dos tipos de câncer mais comum e letal. Neste trabalho, a capacidade das diferentes variantes do algoritmo YOLOv8 foi avaliada na tarefa de segmentação de pólipos, utilizando para isto três bases públicas de imagens de colonoscopia. Dentre as diferentes versões, o YOLOv8n se mostrou a alternativa mais eficaz, apesar de ser a versão mais simples. Os resultados alcançados chegaram à 0,919 de dice e 0,877 de IoU, evidenciando assim a eficácia do modelo.

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