An Automatic Patch-based Approach for HER-2 Scoring in Immunohistochemical Breast Cancer Images Using Color Features

  • Caroline Quadros Cordeiro
  • Sergio Ossamu Ioshii
  • Jeovane Honório Alves
  • Lucas Ferrari de Oliveira
DOI: https://doi.org/10.5753/sbcas.2018.3685

Resumo


Breast cancer (BC) is the most common cancer among women worldwide, approximately 20-25% of BCs are HER-2 positive. Analysis of HER-2 is fundamental to defining the appropriate therapy for patients with breast cancer. Inter-pathologist variability in the test results can affect diagnostic accuracy. The present study intends to propose an automatic scoring HER-2 algorithm. Based on color features, the technique is fully-automated and avoids segmentation, showing a concordance higher than 90% with a pathologist in the experiments realized.

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26/07/2018
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CORDEIRO, Caroline Quadros; IOSHII, Sergio Ossamu; ALVES, Jeovane Honório; DE OLIVEIRA, Lucas Ferrari. An Automatic Patch-based Approach for HER-2 Scoring in Immunohistochemical Breast Cancer Images Using Color Features. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 18. , 2018, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . ISSN 2763-8952. DOI: https://doi.org/10.5753/sbcas.2018.3685.