School of Computer Science

Medical Image Analysis

Professor Ela Claridge, Dr Iain Styles

The research of the medical image analysis group brings together tools, techniques and knowledge from a variety of fields in interdisciplinary work that aims to develop ways of extracting quantitative information about tissues and samples from images. The work involves an understanding of:

The physics of image formation

  • How a structure in the body/sample is transformed into an image?
  • How well do these transformations preserve important features of the structure?
  • How to recover information about the structures from a set of images?

Human visual perception

  • How our visual system groups low level features into coherent entities?
  • What human vision is good at and what are difficult visual tasks?
  • How to engineer practical vision systems inspired by powerful mechanisms developed in natural vision?

Medical diagnosis

  • What visual clues clinicians use for diagnosis?
  • How do they combine visual information in the image with previous experience to arrive at diagnosis?
  • How to model and exploit these abilities to develop practical computer-based aids to diagnosis?

We aim to develop computer tools which assist the clinical expert in difficult visual tasks. Medical imaging domains include dermatology (pigmented skin lesions, or moles), ophthalmology (fundusimages), endoscopy, radiology (X-ray mammography, CT and MRI images of the brain) and fluorescence and optical microscopy.

In collaboration with colleagues working in the area of Natural Computation, we have begun to explore the use of genetic algorithms and evolutionary computation to evolve new methods and operators for image analysis and interpretation. We are also using evolutionary methods to optimise the imaging process itself, using knowledge of the sample and the image formation process to guide the selection of optical wavebands which maximise the accuracy with which we can compute properties of the sample.

The Medical Image Analysis Group maintain a fully-equipped multispectral imaging laboratory, and have extensive experience in acquiring images from a wide variety of samples, both in-vivo and ex-vivo.