Close
Description
Description
This module provides an essential introduction to theory and practice for information processing methods in medical imaging and computing, including the latest developments in machine learning and deep learning medical image processing. The focus of the module is on the registration and segmentation of medical images, alongside an overview of how biomarkers derived from image processing can be used to test scientific hypotheses or applied in clinical contexts. The module also includes a primer on deep learning, which provides a foundation for understanding deep learning approaches to image registration and segmentation. This module assumes a good prior knowledge of basic linear algebra (e.g., matrix arithmetic), calculus, and probability theory, and competent programming skills in Python or Matlab.
Module format
The module comprises conventional lectures, which incorporate interactive discussion elements, and computer laboratory sessions, where the practical elements outlined during the lectures are put into practice, running code to register, segment and statistically analyse medical images.
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
听