Importance of Developing a Decision Support System for Diagnosis of Glaucoma

Glaucoma is a condition of irreversible blindness, but early diagnosis and appropriate interventions can enable patients to see for a longer time. This addresses the importance of developing a decision-support system for glaucoma diagnosis. Glaucoma occurs when pressure happens around the eyes, which causes damage to the optic nerves and deterioration of vision. There are different levels of glaucoma disease including blindness. Diagnosis at an early stage allows a chance for therapies that slows the progression of the disease. By using Optical Coherence Tomography (OCT) images and pattern recognition systems, it is possible to develop a support system for doctors to make decisions on glaucoma. Thus, in this recent study we develop an evaluation and support system for the use of doctors. Computer software based on a pattern recognition system would help doctors to carry out objective evaluations for their patients. It is intended that after carrying out the development and evaluation processes of the software, the system will serve for use by doctors in different hospitals.

[1]  R. P. Mills,et al.  A comparison of experienced clinical observers and statistical tests in detection of progressive visual field loss in glaucoma using automated perimetry. , 1988, Archives of ophthalmology.

[2]  F. Fitzke,et al.  Analysis of visual field progression in glaucoma. , 1996, The British journal of ophthalmology.

[3]  D. Budenz,et al.  Optical coherence tomography platforms and parameters for glaucoma diagnosis and progression , 2016, Current opinion in ophthalmology.

[4]  Weisi Lin,et al.  Learning ECOC Code Matrix for Multiclass Classification with Application to Glaucoma Diagnosis , 2016, Journal of Medical Systems.

[5]  H. Quigley,et al.  The number of people with glaucoma worldwide in 2010 and 2020 , 2006, British Journal of Ophthalmology.

[6]  R A Hitchings Perimetry--back to the future? , 1994, The British journal of ophthalmology.

[7]  C. Krakau,et al.  REGRESSION ANALYSIS OF THE CENTRAL VISUAL FIELD IN CHRONIC GLAUCOMA CASES , 1982, Acta ophthalmologica.

[8]  Huiqi Li,et al.  A model-based approach for automated feature extraction in fundus images , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[9]  C. Krakau,et al.  Visual field decay in normal subjects and in cases of chronic glaucoma , 2004, Albrecht von Graefes Archiv für klinische und experimentelle Ophthalmologie.

[10]  T. Wong,et al.  Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. , 2014, Ophthalmology.