This proposal is in continuation of our previous project which covered analysis of Fundus images for detection of DR and Glaucoma and we have also built a small scale Hospital Management & Information System (HMIS) in that project. This proposal deals with detection of four main eye diseases using a modern imaging technique OCT which is more reliable and can detect diseases at early stages. The diagnostic tools developed in the previous project are being used by the eye specialist at Armed Forces Institute of Ophthalmology (AFIO) Military Hospital Rawalpindi. The iHospital uses ICT technology as a catalyst for effective health care delivery to general public in Pakistan. Its acceptance and support by three main healthcare centers of the country, namely National Institute of Heart Diseases, Armed Forces Institute of Ophthalmology and Shifa International Hospital, stems its effectiveness and viability. The concept attempts to digitize critical medical equipment relating to Cardiology and Ophthalmology, incorporates intelligence for auto diagnostic without the assistance of a medical specialist and net-enabled the equipment for its incorporation as a node in iHospital network. Associated workflow of the specialized hospital is added to ensure its effectiveness in constituting a geographically distributed but unified hospital. The system offers advanced diagnostic to patients by installing the high technology equipment in a center and then giving its access to all hospitals in the network. A central repository stores all records and provides cloud services to all nodes in the network. This is an excellent solution for a developing countries like Pakistan where it has managed the health care in limited budget.
The OCT module of iHospital provides a detailed view of retinal image for analyzing different retinal diseases in their early stages. This covers most of the diseases diagnostic in a complete ophthalmology center. Some retinal diseases like diabetic retinopathy, macular edema, age related macular degeneration and glaucoma are prevalent causes of blindness even in an industrialized world. An eye abnormality caused by the increase of insulin in blood is known as Diabetic retinopathy (DR) and eventually leads to complete vision loss. Macular Edema occurs when fluid deposits (exudates) affect macula causing it to swell and resulting in central vision loss. Age related macular degeneration (AMD) is a medical condition occurs in old age in which yellow deposits called drusen occur in the macula affecting the vision. Glaucoma is an eye disorder associated with increased fluid pressure inside the optic nerve of the retina resulting in permanent damage to the optic nerve causing blindness.
There is a need of awareness among people about different retinal diseases like DR, AMD, Macular edema, Glaucoma. The patients should be regularly monitored or screened in order to save their vision. The ratio of ophthalmologists to eye patients is very low in our country which leads to difficulty in mass screening of various retinal diseases. So incorporation of self-diagnostic system in iHospital is a need for the detection and grading of human retina using digital OCT cameras. The iHospital module that consists of this self-diagnosis system along with high resolution OCT cameras can be placed in a medical centers with trained medical staff for regular screening of different retinal diseases. The system will automatically diagnose the cases that shall then be referred to ophthalmologists if required. The system will also store the medical record of patients visiting any of iHospital module in a secure central repository. The database, designed for this purpose, will be able to store different kind medical records like images, videos, signals and reports etc. This data, once grows, shall become very valuable for mining and finding hidden patterns that can suggest improvement and prevention of diseases, along with giving universal access to patient record for future referrals.
This module of the iHospital will consists of a self diagnosis system for detection of different retinal diseases present in human retina using OCT images and a new software module to incorporate the analysis of OCT images. It is important to highlight that the proposed system will use same basic software for viewing and data handling, hospital management system and basic telemedicine modules which have already been developed in our previous project. This is also evident from the milestones and deliverables which are mostly related to the research work required for analysis of OCT images. Only a few extensions are required in already developed software to accommodate OCT images and large data set. The equipment purchased during our previous project such as desktops and laptops etc will be used in this project and no such equipment will be asked for in this project. The system will take OCT retinal images from OCT camera and will auto-grade it according to abnormalities present using state of the art image processing and pattern recognition techniques. It will also combine the results of OCT analysis with fundus image analysis to improve the validity and reliability of self diagnoses software. The system shall then send only those images and cases to specialist that show possible retinal disease for further diagnosis and the data for each patient will also be saved for regular monitoring and collectively the data shall provide mining tools a wealth of information about public health for effective planning.
The system shall be a part of iHospital and would be incorporated in the system already deployed at AFIO (Armed Forces Institute of Ophthalmology) . The project also proposes to deploy one node of the system in AFIO. It is pertinent to mention here that the team has completed a module that detects DR using fundus images and has incorporated it in iHospital. The project concept has won an exclusive Asia Pacific ICT Alliance Award in the category of R&D in 2012 and the iHospital concept incorporating cardiac and ophthalmology concepts has also secure international recognition while winning APICTA silver Award in R&D Category in 2013 while competing with best R&D projects from 14 different countries in Asia Pacific region these include Australia, Hong Kong, Singapore, Malaysia, Taiwan, Chinese Taipei, etc.
For details of team members, CLICK HERE