Detection & segmentation of anatomical structures in retinal images
The blood vessels, optic disk, fovea and macula are essential anatomical structures in the human retina. The optic disc is the entry and exit site of the blood vessels and optic nerves to the retina. The fovea is a small pit of the retina containing the highest concentration of photosensitive cells and responsible of our highest visual acuity. Both elements can be visualized in retinal images: the optic disc as a bright oval area interrupted by outgoing vessels and the fovea as dark area without retinal capillaries.
Information about the position and the aspect of the optic disk and the fovea helps in the diagnosis and severity grading of several eye complications, such as glaucoma, diabetic retinopathy or age-related macular degeneration. In the presence of severe eye disease manifestations, these structures might be partially or completely obscured in the image, hindering a correct detection and segmentation. We have developed methodologies for automatic detection and segmentation of retinal blood vessels, pathologies including exudates, cotton wool spots e.t.c. This automatic detection and segmentation can be seen as the first step is develop computer assisted diagnostic system for retinal and systemic disease manifested in the eyes.
- Dr Muhammad Moazam Fraz
- Muhammad Abdullah
- Nauman Zahoor
- M. M Fraz, W. Jahangir, S. Zahid, M. M. Hamayun, S. A. Barman , “Multiscale segmentation of exudates in retinal images using contextual cues and ensemble classification”, Biomedical Signal Processing and Control, Vol. 35, pp. 50-62, May, 2017.
- RA Welikala, M.M. Fraz, PJ Foster, PH Whincup, AR Rudnicka, CG Owen, DP Strachan, SA Barman, “Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies”, Computers in Biology and Medicine, Vol. 71, No. 1, pp. 67–76, Apr, 2016.
- M. Abdullah, M.M. Fraz, S.A. Barman, “Localization and segmentation of optic disc in retinal images using Circular Hough transform and Grow Cut algorithm”, PeerJ, Vol. 4, No. 1, pp. 1-23, Apr, 2016.
- M.M. Fraz, R.A. Welikala, A.R. Rudnicka, C.G. Owen, D.P. Strachan, S.A. Barman, “QUARTZ: Quantitative Analysis of Retinal Vessel Topology and size – An automated system for quantification of retinal vessels morphology”, Expert Systems with Applications, Vol. 42, No. 20, pp. 7221, Nov, 2015.
- A. Basit, M.M.Fraz, “Optic disc detection and boundary extraction in retinal images”, Applied Optics, Vol. 54, No. 11, pp. 3440-3447, Apr, 2015.
- M.M. Fraz, A. R. Rudnicka, C. G. Owen, S. A. Barman, “Delineation of blood vessels in paediatric retinal images using decision trees-based ensemble classification.”, International journal of computer assisted radiology and surgery, Vol. 9, No. 5, pp. 795-811, Sep, 2014.
- M.M. Fraz, A. Basit, S. A. Barman, “Application of Morphological Bit Planes in Retinal Blood Vessel Extraction”, Journal of Digital Imaging, Vol. 26, No. 2, pp. 274-286, Apr, 2013.
- M.M. Fraz, P. Remagnino, A. Hoppe, A. Rudnicka, C.G. Owen, P. H. Whincup, S.A. Barman, “Quantification of blood vessel calibre in retinal images of multi-ethnic school children using model based approach”, Computerized Medical Imaging and Graphics, Vol. 37, No. 1, pp. 48-60, Jan, 2013.
- M.M. Fraz, S.A. Barman, P. Remagnino, A. Hoppe, A. Basit, B. Uyyanonvara, A.R. Rudnicka, C.G. Owen, “An approach to localize the retinal blood vessels using bit planes and centerline detection”, Computer Methods and Programs in Biomedicine, Vol. 108, No. 2, pp. 600-616, Nov, 2012.
- M.M. Fraz, P. Remagnino, A. Hoppe, B. Uyyanonvara, A.R. Rudnicka, C.G. Owen, S.A. Barman, “Blood vessel segmentation methodologies in retinal images – A survey”, Computer Methods and Programs in Biomedicine, Vol. 108, No. 1, pp. 407-433, Oct, 2012.
- M.M. Fraz, P. Remagnino, A. Hoppe, B. Uyyanonvara, A.R. Rudnicka, C.G. Owen, S.A. Barman, “An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation”, IEEE Transactions on Biomedical Engineering, Vol. 59, No. 9, pp. 2538-2548, Sep, 2012.