Automatic Grading of Invasive Breast Cancer Patients for the Decision of Therapeutic Plan

This chapter discusses an automatic system designed using whole slide imaging (WSI) and artificial intelligence (AI) technology to grade invasive breast cancer patients enabling therapeutic decisions. This chapter presents an automatic Human epidermal receptor growth factor receptor 2 (HER2) grading system for selecting invasive breast cancer patients for giving HER2 therapy. The system is expected to determine HER2 status automatically and provide useful information to decide on the therapeutic plan, thus improve patient care with optimal therapies. WSI system provides the platform for automated image analysis and diagnosis utilizing AI for digital pathology. The automated cancer grading system can be described in three parts: Specimen preparation, WSI acquisition, and automated HER2 scoring. While the quality evaluation and HER2 quantification requires a high-resolution image. The quality of automated analysis highly depends on the quality of the image used. Using a low-resolution WSI for artifact detection enables faster detection with optimal accuracy.