Medical image computing is an interdisciplinary field at the intersection of computer science, data science, and mathematics, with a wide range of applications to medicine and bioscience. At IIAI, researchers are fully dedicated to applying cutting-edge machine learning and computer vision techniques to revolutionize the healthcare industry through medical image computation and analysis. This involves developing computer-assisted interventional systems and robotics, computer-aided diagnosis systems, and clinical visualization systems, amongst others. All these applications require the manipulation and integration of medical image information. Many applications also depend on the integration of image information with sensor data (e.g. from tracking systems), effector control systems (e.g. robots or positioning devices), visual displays, or other feedback systems. As such, our researchers focus on a broad range of medical imaging applications. For instance, one of our key applications will be destined to mammography, which is a medical imaging technique that uses a low-dose X-ray system to aid in the early detection and diagnosis of breast diseases in women. Advanced deep learning techniques can be applied to detect cancerous lesions much more accurately and efficiently than the traditional examinations by expert radiologists. Another challenging target is Gastrointestinal Infections (GI), where AI-based medical imaging can be deployed to attain highly effective detection and classification. Finally, medical image computing techniques are also used in eye fundus scans for the early detection of diabetes and cardiac disease diagnosis.