Johanna Elisabeth Rogalsky, S. Ioshii, L. F. Oliveira
{"title":"Automatic ER and PR scoring in Immunohistochemistry H-DAB Breast Cancer images","authors":"Johanna Elisabeth Rogalsky, S. Ioshii, L. F. Oliveira","doi":"10.5753/sbcas.2021.16075","DOIUrl":null,"url":null,"abstract":"Breast Cancer (BC) is the most frequently diagnosed cancer for women. This way, the Brazilian Unified Health System (SUS) focuses on studying the disease and improving all the steps involved in dealing with BC. The presence or absence of the Estrogen Receptor (ER) and the Progesterone Receptor (PR), which define invasive subtypes, is detected through Immunohistochemistry (IHC). One way to assist the manual assessment of pathologists and histopathologists is to develop automatic scoring systems. Fortunately, digital pathology is increasingly achieving higher agreement with the pathologist. Therefore we create an automatic scoring system composed of image preprocessing, feature extracting, and classification achieves a 69% f-score rate.","PeriodicalId":413867,"journal":{"name":"Anais do XXI Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS 2021)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais do XXI Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5753/sbcas.2021.16075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Breast Cancer (BC) is the most frequently diagnosed cancer for women. This way, the Brazilian Unified Health System (SUS) focuses on studying the disease and improving all the steps involved in dealing with BC. The presence or absence of the Estrogen Receptor (ER) and the Progesterone Receptor (PR), which define invasive subtypes, is detected through Immunohistochemistry (IHC). One way to assist the manual assessment of pathologists and histopathologists is to develop automatic scoring systems. Fortunately, digital pathology is increasingly achieving higher agreement with the pathologist. Therefore we create an automatic scoring system composed of image preprocessing, feature extracting, and classification achieves a 69% f-score rate.