MPHY0041: Machine Learning in Medical Imaging

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Term 1

This repository is for the deep learning part of the module.

1. Development environments

This repository contains coding tutorials and exercises based on Python. While assuming basic experience in Python programming, learning materials are summarised in the docs folder.

• The supported development environment tools are summarised in module development environment.
• For a refresher, have a look at A Roadmap to Learning Python and Machine Learning by Yourself.
• Module tutorials are implemented in both TensorFlow and PyTorch.
  • Learning TensorFlow for Medical Imaging.
  • Learning PyTorch for Medical Imaging.

2. Deep learning tutorials

Deep learning tutorials are in Python scripts, in the tutorials folder. Individual tutorials may also require other libraries which will be specified in the readme.md in individual tutorial folders (see links below).

• Image classification: Anatomical structure classification on 2D ultrasound images
• Image segmentation: Segmentation of organs on 3D MR images
• Image registration: Unsupervised registration of CT image slices
• Image synthesis: Ultrasound image simulation

3. Formative assessment

A list of tasks are detailed in the Formative Assessment. Complete them for individual tutorials.

4. Reading list

A collection of books and research papers, relevant to deep learning for medical image analysis, is provided in the Reading List.

Contact

Feel free to create an issue for questions or suggestions.

Name	Email	Role
Yipeng Hu	yipeng.hu@ucl.ac.uk	Lecturer
Andre Altmann	a.altmann@ucl.ac.uk	Module Lead