sitting at the border between ophthalmology, neurology and computing science. It is from ... Edinburgh and Dundee and features collaborative input from 10 other research ... generation (training machine learning algorithms) and potentially.
VAMPIRE: Vessel Assessment and Measurement Platform for Images of the REtina Emanuele Trucco, R Annunziata, L Ballerini, E Pellegrini, S J MacKenna
School of Computing, University of Dundee
T MacGillivray, T Pearson, D Relan, G Robertson
Centre for Clinical Brain Science and Clinical Imaging Research Centre, University of Edinburgh
A Doney
FARR Institute, Ninewells Hospital, Dundee
B Dhillon, J Cameron
Princess Alexandra Eye Pavilion, Edinburgh and Anne Rowling Neuroregenerative Clinic, Edinburgh
The black void behind the pupil was optically impenetrable before the invention of the ophthalmoscope by von Helmholtz over 150 years ago. Advances in retinal imaging and image processing, especially over the past decade have opened a route to another unexplored landscape, the retinal neurovascular architecture and the retinal ganglion pathways linking to the central nervous system beyond. Exploiting these research opportunities requires multidisciplinary teams to explore the interface sitting at the border between ophthalmology, neurology and computing science. It is from the detail and depth of retinal phenotyping from which novel metrics and candidate disease biomarkers are likely to emerge. Unlocking this hidden potential requires integration of structural and functional datasets, i.e. multimodal mapping and longitudinal studies spanning the natural history of the disease process. And with further advances in imaging, it is likely that this area of retinal research will remain active and clinically relevant for many years to come. Is against this backdrop that the VAMPIRE project was conceived. It is led by imaging scientists and clinicians from the Universities of Edinburgh and Dundee and features collaborative input from 10 other research centres in Italy, Singapore, Australia, Japan and the US. With funding from EPSRC, MRC, Leverhulme Trust, Optos plc and the EU, we are translating cutting-edge image processing and analysis to the clinical research environment to deliver software that users without specialist knowledge can apply easily to their images to generate valuable data that they normally would not have been able to obtain. To date, our software has been used to analyse more than 10,000 images in studies investigating retinal biomarkers for cardiovascular disease [11], diabetes, stroke, MS, cerebral malaria, and age-related cognitive change. VAMPIRE has been the first software tool ever to analyse retinal images from UK Biobank.
Neurodegenerative associations, e.g., MS, are being investigated as well within an MRC CASE project. Generation of synthetic retinal images. We are developing a system based on machine learning and computer graphics techniques with the aim to generate realistic fundus images parameterized by content, which could be extremely useful for ground truth generation (training machine learning algorithms) and potentially for training junior specialists with larger-than-normal collections of images [5]. Analysis of the corneal nerve fibre layer and allied biomarkers. This stream is developing software tools for the automatic segmentation of corneal nerve fibres in microscopy images, and to assess density and tortuosity. The latter are being investigated as potential biomarkers is a variety of conditions in collaboration with the Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston [10].
ACKNOWLEDGMENTS: VAMPIRE is funded by EPSRC, MRC, the Leverhume Trust, EU Framework VII ITN "REVAMMAD", Optos Plc, and SINAPSE. We thank Dr Jim Wilson (Population Health, Univ of Edinburgh) for granting access to the ORCADES data set, Dr Alex Doney (co-author, Univ of Dundee) for organizing access to GoDARTS, and Prof Ian Deary (CCACE, Univ of Edinburgh) for granting access to the Lothian Birth Cohort.
[1] http://diabetesgenetics.dundee.ac.uk/ [2] www.orcades.ed.ac.uk/orcades [3] medicine.dundee.ac.uk/tascforce [4] http://www.trialsjournal.com/content/13/1/184 [5] S. Fiorini, M. De Biasi, L. Ballerini, E. Trucco, A. Ruggeri, Automatic Generation of Synthetic Retinal Fundus We propose a poster or a talk illustrating the VAMPIRE constellation of Images, Proc. Smart Tools \& Apps for Graphics (STAG), Cagliari, activities, some of which are summarized below. Italy, September 2014. Software tools for retinal image analysi in fundus images. The team [6] A. Lisowska, R. Annunziata, E. Trucco, D. Karl, G. K. Loh, An has been growing since 2007 the VAMPIRE software tool for Experimental Assessment of Five Indices of Retinal Vessel semi-automatic measurement of morphometric properties of the Tortuosity with the RET-TORT Public Dataset, in 35th Annual retinal vasculature, including conventional ones like artery-vein International Conference of the IEEE EMBS Engineering in classification, calibre, tortuosity, CRVE/CRAE and AVR, but also Medicine and Biology Society (EMBC), pp. 5414-5417, Chicago, fractal dimension and angles at junctions [6,7]. USA, 2014. Software tools for retinal image analysis for ultra-wide-field-of[7] D. Relan, T. MacGillivray, L. Ballerini, E. Trucco, Automatic view SLO images. This stream aims to develop the equivalent of the Retinal vessel classification using a Least Square-Support Vector VAMPIRE software tools for UWFV SLO images, provided by Machine in VAMPIRE, in 35th Annual International Conference of industrial collaborator OPTOS plc. VAMPIRE has received the IEEE EMBS Engineering in Medicine and Biology Society uninterrupted funding from OPTOS since 2002. Target (EMBC), pp. 142-145, Chicago, USA, 2014. measurements include morphometric properties as in fundus [8] E. Pellegrini, G. Robertson, E. Trucco, T. J. MacGillivray, C. images above, but also quantification of vascular lesions in Lupascu, J. v. Hemert, M. C. Williams, D. E. Newby, E. J. v. Beek, fluorescein angiogram exams (leakage, nonperfusion) [8,9]. G. Houston, Blood vessel segmentation and width estimation in Discovery of retinal biomarkers for systemic conditions. The ultra-wide field scanning laser ophthalmoscopy, Biomed. Opt. current version of the fundus-image tool (VAMPIRE 3.0) is being Express, vol. 5, no. 12, pp. 4329-4337, 2014. used to measure most of the above in two cross-linked data sets [10] R. Annunziata, A. Kheirkhah, S. Aggarwal, B. Cavalcanti, P. with clinical and genetic data, GoDARTS [1] and ORCADES [2], Hamrah, E. Trucco, Tortuosity classification of corneal nerves each with n ~= 2,000, in a study funded by the Leverhulme Trust. images using a multiple-scale-multiple-window approach, in SLO analysis software is being used in a study investigating retinal Proceedings of the Ophthalmic Medical Image Analysis (OMIA) biomarkers for cardiovascular disease, attached to two major First International Workshop, MICCAI 2014, pp. 113-120, Boston, Scottish studies, TASCFORCE [3] in Tayside and SCOT-HEART USA, 2014. [4] (pan-Scotland). A recently awarded EPSRC project, starting [11] T. J. MacGillivray, E. Trucco, J. R. Cameron, B. Dhillon, J. G. April 2015, will investigate multi-modal retinal biomarkers for Houston, E. J. R. van Beek,Retinal imaging as a source of vascular dementia, in collaboration with the Centre for Clinical biomarkers for diagnosis, characterization and prognosis of chronic Brain Science in Edinburgh and Ninewells Hospital in Dundee. illness or long-term conditions, The British Journal of Radiology, vol. 87, no. 1040, pp. 20130832, 2014.
