Current projects

This research is concerned with the characterisation of pigmented skin lesions to help with early diagnosis of malignant melanoma, a skin cancer. Out group has developed a novel image analysis method which uses physics-based modelling of optical properties of the skin. The method computes parametric maps characterising skin structure and composition. The images show histological quantities in the skin, such as concentration of pigment melanin, concentration of blood and thickness of collagenous tissue. They also show whether melanin is present in the dermis - such presence is a very sensitive indicator of melanoma. SIAscope is a clinical device based on this research, developed by Astron Clinica and used in dermatology clinics in UK and beyond. See parametric maps for melanoma Further information

The goal of the project is to formulate a generic approach to image interpretation based on the spectral characterisation models. This should enable the structure and composition of the materials and tissues to be deduced from their images acquired through a small number of optical filters using a standard digital camera. Further information

This project aims to develop and validate a new physics based image interpretation method for the ocular fundus and to evaluate its potential in detecting early signs of diabetic retinopathies. An understanding of the physical interaction of light with ocular tissue is utilised to formulate a mathematical model capable of predicting colours which correspond to different tissue composition. Colours in digitized clinical images will be interpreted through reference to this model, generating "retinal maps" which show separately the quantities and distribution of blood, retinal pigment and pathological exudates at every image point. Further information

A clinical study using the SIAscope images for diagnosis of malignant melanoma has shown that the presence of blood depravation regions within the lesion is strongly associated with malignancy. This project has developed a computer method for automatic detection of the blood deprived regions. The results of the computer method compared to clinical assessment show very good agreement, with 91% sensitivity and 96% specificity on the set of 95 lesions.

The sharpness of the lesion boundary and the contrast between the lesion and the surrounding skin provide important diagnostic information in the assessment of pigmented skin lesions. This project has developed a new method for computing these parameters by employing an edge model based on a sigmoid function. For each point on the lesion boundary, optimal parameters are found by using an interative least-squares method. One of the parameters returned is the location equivalent to "zero crossing" for each boundary profile. A collection of these points demarkates the lesion boundary.

Whereas most algorithms for symmetry computation are designed to find the best axis of symmetry, in this work we are interested in finding the degree of symmetry for the lesion pattern. Instead of choosing the best symmetry axis, a number of putative symmetry axes are considered and scored. The variability of these scores characterizes the overall symmetry of the lesion. Symmetry scores can be computed for both the lesion shape and for the pattern of pigmentation within the lesion. The latter is computed by removing low-frequency variations underlying the transition from the lesion body to the skin outside.

Completed projects

• Colour and pigmentation analysis in skin lesions
  with Symon Cotton and Per Hall (Adenbrooke's Hospital, Cambridge)
  

• Characterisation of visual features in skin lesions
  with Jon Morris Smith and Per Hall (Adenbrooke's Hospital, Cambridge) "Image and signal based analysis of pigmented skin lesions", March 1998).
• Low-level boundary grouping mechanisms for contour completion
  with Alison Todman, School of Computer Science

• Characterisation of mammographic lesions
  with Josef Richter, School of Computer Science
• Computational and psychophysical approaches to contour perception
  with School of Psychology and Hamburg University
• Image registration
  with Mutawarra Hussain , School of Computer Science
• Medical workstation for neuromedicine
  with Queen Elizabeth Hospital, Birmingham