Computer Aided Diagnosis System

Computer-aided diagnosis (CAD) systems aim to improve medical diagnosis by automating the analysis of medical images, assisting clinicians in tasks like lesion classification and segmentation. Current research emphasizes developing robust and interpretable CAD systems using deep learning architectures such as convolutional neural networks (2D and 3D), incorporating techniques like self-supervised learning and multi-task learning to improve accuracy and efficiency. These advancements are significant because they can lead to faster, more accurate diagnoses, potentially reducing healthcare costs and improving patient outcomes across various medical specialties, including ophthalmology, pulmonology, and radiology.