Sarah Barman, School of Computer Science and Mathematics, Kingston University, will give a talk on Wednesday, June 20, 2018.
Title :Quantifying the retinal vasculature in the UK Biobank fundus camera images
Abstract : The application of image analysis techniques to provide accurate measures of image features on larger datasets presents specific challenges in ensuring the reliability of the measurements produced. The sizes of current retinal fundus image datasets are increasing, and with their public availability there is increased scope for computer vision researchers to apply algorithms to datasets with variable image characteristics. Image datasets may exhibit variation in terms of image quality, and in terms of image characteristics, such as sets of fundus images that display a range of pathologies. The presentation will report on the experience of applying computer vision techniques to analyse the UK Biobank retinal fundus dataset that contains over 100,000 images. The analysis included recognition of the retinal vasculature, including classification of arterioles and venules, and the provision of vessel morphometric data across the retinal image. The presentation will discuss the experience in terms of generation of reliable data and will report on the challenges in addition to the overall approach that was taken.