Medical Image Analysis and Computer Aided Diagnosis (CAD) systems, in close development with novel imaging techniques, have revolutionised healthcare in recent years. Those developments have allowed doctors to achieve a much more accurate diagnosis, at an early stage, of the most important diseases. Technology behind the development of CAD systems stems from various research areas in computer science such as: artificial intelligence, machine learning, pattern recognition, computer vision, image processing and sensors and acquisition. There is a clear lack of MSc studies which cover the previously mentioned areas with a specific application to the analysis of medical images and development of CAD systems within an integrated medical imaging background. Moreover, the medical technology industry has detected a growing need of expert graduates in this field.
Join MAIA to be part of this revolution and impact your career!
The master programme is part of the UBFC Graduate Schools Engineering and Innovation through Physical Sciences and High-technologies (EIPHI), and Innovative Therapies (INTHERAPI) which also include a doctoral programme in the same topics.
Almost half of the programme is devoted to research project (3 month during the first year) & internship (5 months during the second year) in an international research team, leading to a master thesis aiming at the standards of a research article.
The overall objective is to start from science fundamentals, low-level image and signal processing and acquisition. The second semester is devoted to more advanced image processing algorithms along with machine learning and pattern recognition. Special emphasis will be given to fundamentals of medical robotics and algorithm optimization methods. The third semester will take advantage of the previous modules and will focus on developing frameworks of computer aided detection and diagnosis systems with special emphasis to its clinical applicability and evaluation. In addition, advanced medical robotics will be covered taking into account computer aided surgery and assisted intervention. In addition a project on medical imaging wil proposed which will put those topics into practice. The final semester will be fully devoted to the development of the master thesis in a topic proposed by the consortium, collaborating companies/research labs or by the motivation of the student within the context of medical image analysis.
An induction week is organized each year in September during which the enrolled students are informed about the programme, the assessment and the rules. The induction week also permits new students to meet second-year students or former MaIA students.
Introduction to Image Processing
Digital Signal Processing
Sensors and Digitization
Machine and Deep Learning
Introduction to Robotics
Statistical Learning and Data Mining
Distributed Programming and Networking
Advanced Image Analysis
Medical Image Registration and Applications
Medical Image Segmentation and Applications
Computer Aided Surgery and Medical Robotics
Computer Aided Diagnosis
|Research Internship in a company or any of the partners institutions UdG, uB or UNICLAM|
Scholarships will be awarded each year to high quality foreign students.
Contact: David Fofi