Y. Quan, J. Cheng, B. H. Lee, A. P. Yow and D. W. K. Wong, "Automatic glaucoma screening hybrid cloud system with pattern classification algorithms," 2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP), Singapore, 2017, pp. 219-222. doi: 10.1109/SIPROCESS.2017.8124536
Glaucoma, which is known as the "Sneak thief of sight", is chronic and gradually weakens vision in the unknowing patient. There are no obvious symptoms during early stage of glaucoma, at which time it can only be diagnosed by regular eye diagnosis. Early detection of glaucoma associated with timely treatment has been shown to prevent blindness and visual loss. Quite recently, considerable attention has been paid to the combination between automatic glaucoma screening and hybrid cloud technology. This paper presents a platform which provides automatic glaucoma screening service based on hybrid cloud framework. A novel pattern classification technique was proposed for cup to disc ratio (CDR) assessment using 2-D retinal fundus images and it uses the reconstruction coefficients from SDC to compute the CDR. The proposed technique is used in the glaucoma screening diagnosis module of the remote hybrid cloud system. The scalability and flexibility of hybrid cloud framework enable the platform to work as moving connectivity between patients and ophthalmologists. The system enables the patients to get remote diagnostics from distance with low-cost and blindness and visual loss can be prevented through early detection and timely management.