Artificial intelligence (AI) and machine learning (ML), especially deep learning, have generated tremendous impacts throughout our society, including the tomographic medical imaging field. In contrast to computer vision and image analysis, which have been major application examples of deep learning and deal with existing images, tomographic medical imaging mainly produces cross-sectional or volumetric images of internal structures from sensor measurements. Recently, deep learning has started being actively developed worldwide for medical imaging, including both tomographic reconstruction and image analysis. While medical imaging is a well-established field, in which extensive teaching experience has been accumulated over the past few decades, updating the medical imaging course to reflect AI/ML influence is a new challenge given the rapidly changing landscape of AI-based medical imaging, particularly deep tomographic imaging.

Medical image analysis is a highly empirical discipline, with an emphasis on strong understanding and coding ability. I will oversee students' progress when the term project is announced to make sure the quality of students' deliverables. I also set up the examination on the basic concepts.