Development of Retina Healthcare Service System Using Smart Phone

Abstract

In this paper, we have developed a Retina Healthcare Service System through which the patient himself/herself can manage his/her retina health. In the case of conventional portable ophthalmic cameras, patients cannot check their eye health on their own because most of them are used by doctor in environments where ophthalmography cannot be performed properly. This system consists of web, app and camera modules, and when a patient mounts a camera module for fundus photography on his / her smart phone and then photographs his / her fundus through the app, the image is transmitted to a server, and the transmitted image reads the fundus the patient's fundus image status in the fundus image reading model learned using deep learning. When the doctor expresses his/her opinions about the patient 's eye condition based on the reading result and the fundus photograph, the patient can check through the app and judge whether to receive ophthalmologic treatment.

Figure 1. Increase Trends of Glaucoma and Diabetic Retinopathy by 2050

Figure 2. System Configuration Diagram

Figure 3. IR LED Lighting

Figure 4. Before Assembling The Camera Module

Figure 6. App Configuration Diagram

Figure 7. Main Screen

Figure 10. Funds List Taken

Figure 11. Image Selection and Comments(Doctor’s Opinion)

Figure 12. Web Configuration Diagram

Figure 13. Main Screen

Figure 14. Login Screen

Figure 15. List of Member Fundus photos

Figure 17. Configuration of learning System application system

Figure 16. Fundus Examination andComments

Figure 18. Main function processes

Figure 19. Mounting The Camera Module(1)

Figure 21. App Login Screen

Figure 24. Fundus Photographing

Figure 25. Saving the shot Picture

Figure 26. Web page – Patient management Menu on the main screen

Figure 28. Fundus Image determined as Normal and writing A doctor’s opinion (Comment)

Figure 30. App ExaminationRecord screen

Figure 31. App Doctor’sComment screen

Figure 5. After Assembling The Camera Module

Figure 8. Fundus Examination Screen

Figure 9. Fundus Photographing

Figure 20. Mounting The Camera Module(2)

Figure 22. App Menu Screen

Figure 23. App Fundus Examination Screen

Figure 27. List of fundus images taken By the patient

Figure 29. Fundus Image determined as Abnormal and writing A doctor’s opinion (Comment)

Table 1. Results of learning model test (Excluding images)