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

Caroline Q. Cordeiro and Sergio O. Ioshii and Jeovane H. Alves and Lucas F. Oliveira
2018 arXiv   pre-print
Breast cancer (BC) is the most common cancer among women world-wide, 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.
arXiv:1805.05392v1 fatcat:rqozr32nrjdgdoywptwn5jtd6u