Deep learning for medical image segmentation and reconstruction
Background: Over the last decade, machine learning techniques have demonstrated the potential to learn complex models and information from images. Deep learning in particular has been shown to be a powerful tool in computer vision applications such as image classification or face recognition. However, the application of deep learning in medical imaging is challenging due to the large size of the images (millions of voxels in 3D or 4D) and the small size of the training databases.
Challenge: The aim of this project is two-fold:
- To implement deep learning techniques to build generative models from medical images.
- To use the generative models for image segmentation and reconstruction.
Skills: The project will require a good understanding of machine learning techniques as well as some knowledge of computer vision. The project also requires very good programming skills.
Visualization of massive-scale medical image datasets
Background: UK Biobank is the world’s largest population health study, collecting health and lifestyle records from over 500,000 subjects in the UK. For a subset of 100,000 subjects UK Biobank is also collecting medical images in form of Magnetic Resonance Images (MRI) of the brain, heart and whole-body. State-of-the-art machine learning techniques for dimensionality reduction such as manifold learning provide powerful approaches to uncover the relationship between images (i.e. their similarities and dissimilarities). However, the intuitive visualization of these relationships is still challenging.
Challenge: The aim of this project is three-fold:
- To implement state-of-the-art dimensionality reduction techniques for massive-scale medical image datasets such as UK Biobank.
- To explore visualization techniques for massive-scale medical image datasets such as UK Biobank to allow the user to interactively query the image databases
- To implement a web-based user interface for visualization using the facilities of the visualization studio of the Data Science Institute at Imperial.
Skills: The project will require a good understanding of machine learning techniques as well as some knowledge of computer graphics and/or computer vision. The project also requires very good programming skills.