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Clinical Ophthalmology: A Systematic Approach
TLDR
Ocular side-effects of systemic medication 21.1.Abstract:
1. Eyelids 2. Lacrimal Drainage System 3. Orbit 4. Dry Eye Disorders 5. Conjunctiva 6. Cornea 7. Corneal and Refractive Surgery 8. Episclera and Sclera 9. Lens 10. Glaucoma 11. Uveitis 12. Ocular Tumours 13. Retinal Vascular Disease 14. Acquired Macular Disorders 15. Hereditary Fundus Dystrophies 16. Retinal Detachment 17. Vitreous Opacities 18. Strabismus 19. Neuro-ophthalmology 20. Ocular side-effects of systemic medication 21. Trauma Indexread more
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Proceedings Article
Segmentation of retinal blood vessels based on analysis of the hessian matrix and Clustering Algorithm
TL;DR: A novel unsupervised method to segment retinal blood vessels from colour fundus images is proposed, and a new vesselness measure is introduced which is based on detecting vessel centerlines and orientation in scale space.
Journal ArticleDOI
Differences in reading performance of patients with Drusen maculopathy and subretinal fibrosis after CNV
TL;DR: Despite comparable results in distance visual acuity, patients with subretinal fibrosis after CNV had a greater reduction in reading ability than the patients with drusen, and the distanceVisual acuity measurements alone should underestimate the real-life conditions and impact of AMD.
Journal ArticleDOI
Encoder Enhanced Atrous (EEA) Unet architecture for Retinal Blood vessel segmentation
V. Sathananthavathi,G. Indumathi +1 more
TL;DR: In this paper, an encoder enhanced Atrous architecture is proposed for retinal blood vessel segmentation, which improves the depth concatenation process with the addition layers of the encoder.
Journal ArticleDOI
Uses and safety profile of ciclosporin in ophthalmology.
Shahram Kashani,Ali A. Mearza +1 more
TL;DR: The uses and safety profile of systemic and topical ciclosporin in ophthalmology are reviewed, as well as discussing alternative therapeutic agents available.
Proceedings ArticleDOI
Blood vessels segmentation in nonmydriatic images using wavelets and statistical classifiers
TL;DR: A new framework for automatic analysis of optic fundus nonmydriatic images is described, focusing on the segmentation of the blood vessels by using pixel classification based on pattern recognition techniques, allowing noise filtering and blood vessel enhancement in a single step.