Master MVA DLMI

Piazza access for registered students

Medical imaging technologies provide unparalleled means to study structure and function of the human body in vivo. Interpretation of medical images is difficult due to the need to take into account three-dimensional, time-varying information from multiple types of medical images. Artificial intelligence (AI) holds great promises for assisting in the interpretation and medical imaging is one of the areas where AI is expected to lead to the most important successes. In the past years, deep learning technologies have led to impressive advances in medical image processing and interpretation.

This course covers both theoretical and practical aspects of deep learning for medical imaging. It covers the main tasks involved in medical image analysis (classification, segmentation, registration, generative models…) for which state-of-the-art deep learning techniques are presented, alongside some more traditional image processing and machine learning approaches. Examples of different types of medical imaging applications (brain, cardiac…) will also be provided.

Course location

Online or CentraleSupelec

Lectures

1. Introduction to medical imaging
14/01 at 13h45
2. Classification (with lab)
21/01 at 13h45
3. Validation, interpretation and reproducibility (with lab)
28/01 at 13h45
4. Detection (with lab)
04/02 at 13h45
5. Segmentation (with lab)
23/02 at 13h45
6. Generative models (autoencoders, GANs) (with lab)
09/03 at 13h45
7. Denoising and reconstruction (with lab)
26/03 at 13h45
8. Registration (with lab)
02/04 at 13h45