Diagnosing retinal diseases at their earliest stage can save a patient’s vision since, at an early stage,
the diseases are more likely to be treatable. However, ensuring regular retina checkups for each citizen by
ophthalmologists is infeasible not only in developing countries with huge populations but also in developed
countries with small populations. The main reason is that the number of ophthalmologists compared to
citizens is very small. It is particularly true for low-income and low-middle-income countries with huge
populations, such as Bangladesh and India. For example, according to a survey by the International Council
of Ophthalmology (ICO) in 2010, there were only four ophthalmologists per million people in Bangladesh. For
India, the number was 11. Even for high-income countries with a small population, such as Switzerland and
Norway, the numbers of ophthalmologists per million were not very high (91 and 68, respectively). More than
a decade later, in 2021, these numbers remain roughly the same. Moreover, 60+ people (who are generally at
high risk of retinal diseases) are increasing in most countries. The shortage of ophthalmologists and the
necessity of regular retina checkups at low cost inspired researchers to develop computer-aided systems to
detect retinal diseases automatically. Developed countries like the USA, the United Kingdom, and Germany
have already started using automatic systems for diabetic retinopathy detection. In Bangladesh, BIRDEM
hospital uses an automatic system for detecting Glaucoma. BioMe is trying to develop an automatic system not
only for Glaucoma but also for diabetic retinopathy. The reason behind developing an automatic system is not
to replace retina specialists but instead to reduce the burden of retina specialists. For regular checkups,
patients will take help from the automatic system, and patients with serious retina problems will take
suggestions from retina specialists.
Until now, retina biometric systems used to authenticate persons for giving access to highly confidential
areas such as secured databases, military zones, and airports are the same side systems. That means they use
the same side retina for the registration and authentication stages. BioMe is working on developing a system
by which any side retina can be used to recognize persons.
Multi-session Colored Fundus Image (MCFI) database is the pre-requisite for developing SIRBBS, retina
registration, detecting progress of pathology in retina, and reference image-based quality assessment of
fundus images. Most of the publicly available databases have single-session data. No publicly available
database has multi-session fundus images taken from both sides of the eyes of a statistically sufficient
number of subjects. Therefore, researchers working in retina-based research have to apply different kinds of
data augmentation techniques, which can compensate for the lack of multi-session data in a naive way but
fails to give complete confidence to the researchers about their results. BioMe’s MCFI database will help
researchers to dig into different areas of retina in more detail and with more confidence.