Advances In Machine Learning For Computer-aided Diagnosis In Biomedical Imaging

This article discusses the importance of early detection and diagnosis of cancer, which is the second most common cause of death in many countries. It explains how computer-aided diagnosis (CAD) systems can be used as a second opinion system to diagnose ambiguous cases, using classical image processing, computer vision, machine learning, and deep learning methods for image analysis. The article focuses on advanced CAD methods that use artificial intelligence (AI) approaches in various imaging modalities, such as x-ray, computed tomography (CT), positron emission tomography (PET), ultrasound, MRI, immunohistochemistry, and hematoxylin and eosin (H&E) whole slide images (WSIs), toward the end diagnosis or prognosis.