Prof Ela Claridge

Current research

Retinal imaging

An understanding of the physical interaction of light with ocular tissue is utilised to formulate a mathematical model capable of relating colours to retinal histology. Retinal maps showing the quantities and distribution of haemoglobins and macular pigment help with diagnosis of diabetic retinopathies and Age-related Macular Degeneration. Skin and skin cancer

As an aid for early diagnosis of skin cancers we have developed novel image analysis methods which use physics-based modelling of optical properties of the skin to compute quantitative maps of of pigment melanin, concentration of blood and thickness of collagenous tissue. The presence of melanin in the dermis is a very sensitive indicator of melanoma.

Colon cancers

Histological parameters characterising the colon tissue are computed from multispectral images of the colon and presented as parametric maps. Cancerous tissue shows much increased blood volume fraction and different collagen density in comparison to the normal colon.

Quantitative microscopy

Quantitative information derived from images generated by a variety of microscopic techniques (fluorescent microscopy, TIRF, DIC and their combinations) supports research in cancer, auto-immune diseases, cardiovascular diseases and drug development.


Rheumatoid arthritis can cause destruction or deformation of cartilage and bone. By comparing CT data of a pathological sample to a statistical model of non-pathological bone shape variations the nature and extent of bone destruction can be determined.

Imaging systems

Theoretical modelling of light interaction with tissues often suggests the design of novel imaging systems optimised for specific diagnostic targets. Our work in this area benefited skin cancer imaging and retinal imaging.

Some earlier projects

Image interpretation via material specific spectral characterisation models
Funded by the Leverhulme Trust
Automatic detection of blood deprived regions in parametric images of the skin
with Francesca Satta, Florence University
Modelling of edge profiles in pigmented skin lesions
with Tim Lee, Cancer Research Institute, Vancouver, Canada
Symmetry analysis