Artificial intelligence in automatic classification of invasive ductal carcinoma breast cancer in digital pathology images
Mohammad Abdolahi, Mohammad Salehi, Iman Shokatian, Reza Reiazi
Abstract
Background: Breast cancer is one of the most causes of death in women. Early diagnosis and detection of Invasive Ductal Carcinoma (IDC) is an important key for the treatment of IDC. Computer-aided approaches have great potential to improve diagnosis accuracy. In this paper, we proposed a deep learning-based method for the automatic classification of IDC in whole slide images (WSI) of breast cancer. Furthermore, different types of deep neural networks training such as training from scratch and transfer learning to classify IDC were evaluated.
Topics & Concepts
Ductal carcinomaBreast cancerPathologyInvasive ductal carcinomaDigital pathologyMedicineCancerCarcinomaInternal medicineAI in cancer detectionRadiomics and Machine Learning in Medical Imaging