Medical imaging, specifically radiologic imaging is the most commonly used diagnostic tool for disease diagnosis and treatment assessment for a wide variety of conditions. Over the last decades the image acquisition hardware has improved significantly and corresponding image reconstruction software has become more sophisticated. These provide increasingly complex data both in terms of size and content, making it a challenging task for radiologists to sift through and arrive at meaningful diagnosis and therapeutic assessment. The role of AI/ML techniques in this context is to act as a radiologist’s assistant to automate routine tasks and provide preliminary diagnosis. A radiologist can then use the outputs from these systems to speed up and improve accuracy of diagnosis.