Medical Image Segmentation

About this programme

Welcome to the course CM2002 Artificial Intelligence within Biomedical Engineering and Health Systems ! During this course you will experience various aspects of current, emerging and future healthcare challenges and trends, learn how to develop innovative technical solutions and recognise business opportunities. Various activities include but not limited to lectures, team collaboration, oral presentations, study visits, problem based learning seminars, practical hands on training and collaborative project work. By the end of this course, you will have relevant knowledge on how new technologies can tackle future challenges in healthcare, appreciate the benefits, but also understand the barriers and risks associated with the implementation of the innovative solution. The content of the course is also part of the Professional development in the form of life-long learning to be offered to innovators and entrepreneurs, healthcare professionals, medical engineers and policy makers. Please note that Students not located in Sweden may have problems attending a course at KTH. You could meet obstacles if you're required to pay fees or if you do not have a Swedish Mobile BankID. Please note: all information from the Course syllabus is available on this page in an accessible format. The course consists of lectures, laboratories, mathematical exercises, and an exam. Participants combine basic and advanced software libraries for image registration in Python, including scipy, numpy, SimpleITK, scikit-image, etc. Some specific labs use MATLAB and Mialab, an image segmentation tool deve