  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.
