• Zu Quan Ik Department of Computing and Information Systems, Faculty of Science and Technology, Sunway University, Bandar Sunway, Malaysia
  • Sian Lun Lau Department of Computing and Information Systems, Faculty of Science and Technology, Sunway University, Bandar Sunway, Malaysia
  • Jan Bond Chan Department of Ophthalmology, School of Medical Sciences, Universiti Sains Malaysia, Kelantan, Malaysia



Cataract detection, medical screening mobile application


The cataract is the leading cause of blindness and affecting nearly 22 million Americans aged 40 and older. Cataract screening is a process usually carries out by an ophthalmologist using specialize equipment. The hurdles that we are facing today to screen for cataract include the availability of medical practitioner and proper equipment, especially in the rural area. Other problems include the cost and time involved to do eye examination from the medical practitioner. In this paper, we aim to research on an alternate cataract screening solution using a flash-enabled smartphone without any external attachments. The solution should be made usable by general public. The research is divided into three different phases. The first phase aims to understand how medical practitioner performs cataract screening using red reflex and attempts to replicate it using mobile application. The second phase involves collecting data to obtain the appropriate parameters that allow replication of red reflex using mobile application. The third phase of this research intends to replicate the Ophthalmologist diagnosis using Artificial intelligent built into the mobile application. This paper presents the work performed and the obtained outcome from the first and second phases.


N. E. Institute, Facts About Cataract, Facts, Last Accessed 30th June 2015.

W. H. Organization, Prevention of Blindness and Visual Impairment,, Last Accessed 30th June 2015.

A. A. 2010. of Ophthalmology, Cataract Surgery Saves Lives, Dollars by Reducing Auto Crashes, cataract-surgery-saves-lives-dollars-by-reducing-a, Last Accessed 30th June 2015,

V. Tseng, F. Yu, F. Lum, and A. Coleman. 2012. Risk of Fractures Following Cataract Surgery in Medicare Beneficiaries, JAMA. 308(5): 493–501, [Online]. Available: +

A. A. 2011. of Ophthalmology, Eye Health Statistics at A Glance,, Last Accessed 24th November 2014

I. Litmanovitz and T. Dolfin, 2010. Red Reflex Examination In Neonates: The Need for Early Screening, Isr Med Assoc J, 12(5): 301–302,

M. B. Datiles, P. A. Edwards, B. L. Trus, and S. B. Green, 1987. In Vivo Studies on Cataracts Using The Scheimpflug Slit Lamp Camera. Investigative Ophthalmology & Visual Science. 28(10): 1707. [Online]. Available: +

A. A. 2008. of Pediatrics et al., Red Reflex Examination in Neonates, Infants, and Children, Pediatrics. 122(6): 1401–1404,

S. Wang, X. Zhao, I. Khimji, R. Akbas, W. Qiu, D. Edwards, D. W. Cramer, B. Ye, and U. Demirci, 2011. Integration of Cell Phone Imaging with Microchip Elisa To Detect Ovarian Cancer He4 Biomarker in Urine at The Point-Of-Care, Lab on a chip. 11(20): 3411–3418. [Online]. Available:

D. Tseng, O. Mudanyali, C. Oztoprak, S. O. Isikman, I. Sencan, O. Yaglidere, and A. Ozcan, 2010. Lensfree Microscopy on A Cellphone, Lab Chip. 10: 1787–1792. [Online]. Available:

S. Kroemer, J. Frhauf, T. Campbell, C. Massone, G. Schwantzer, H. Soyer, and R. Hofmann-Wellenhof, 2011. Mobile Teledermatology For Skin Tumour Screening: Diagnostic Accuracy of Clinical and Dermoscopic Image Tele-Evaluation using Cellular Phones, British Journal of Dermatology. 164(5): 973–979. [Online]. Available:

C.-H. Hsieh, H.-H. Tsai, J.-W. Yin, C.-Y. Chen, J. C.-S. Yang, and S.-F. Jeng. 2004. Teleconsultation with The Mobile Camera-Phone in Digital Soft-Tissue Injury: A Feasibility Study, Plastic and Re-constructive Surgery. 114(7): 1776–1782

V. F. Pamplona, A. Mohan, M. M. Oliveira, and R. Raskar, 2010. Netra: Interactive Display for Estimating Refractive Errors and Focal Range, ACM Trans. Graph. 29(4): 77:1–77:8, Jul. [Online]. Available:

V. F. Pamplona, E. B. Passos, J. Zizka, M. M. Oliveira, E. Lawson, E. Clua, and R. Raskar. 2011. Catra: Interactive Measuring and Modeling of Cataracts, in ACM SIGGRAPH 2011 Papers, ser. SIGGRAPH’11. New York, NY, USA: ACM. 47:1–47:8. [Online]. Available:

J. B. Chan, H. C. Ho, N. F. Ngah, and E. Hussein. 2014. DIY - Smartphone Slit-Lamp Adaptor, Journal of Mobile Technology In Medicine. 3(1): 16–22,.

A. Bourouis, M. Feham, M.A. Hossain, L. Zhang. 2014. An Intelligent Mobile Based Decision Support System for Retinal Disease Diagnosis Decision Support Systems. 59: 341-350

de la Torre-Díez, Isabel, et al. 2015. Decision Support Systems and Applications in Ophthalmology: Literature and Commercial Review Focused on Mobile Apps. Journal of medical systems 39(1): 1-10.

Prasanna, Prateek, et al. 2013. Decision Support System for Detection of Diabetic Retinopathy Using Smartphones. Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2013 7th International Conference on. IEEE

Myung, David, et al. 2014. D Printed Smartphone Indirect Lens Adapter for Rapid, High Quality Retinal Imaging. Journal of Mobile Technology in Medicine 3(1): 9-15.

Hu, X-P., L. Dempere-Marco, and G-Z. Yang. 2003. Hot Spot Detection Based On Feature Space Representation of Visual Search in Medical Imaging. Information Technology Applications in Biomedicine, 2003. 4th International IEEE EMBS Special Topic Conference on. IEEE




How to Cite