Researchers at Arizona State University are harnessing the power of artificial intelligence to aid in the diagnosis of myopic maculopathy, a serious and irreversible eye disease that is on the rise globally. Led by Professor Yalin Wang, a team from the School of Computing and Augmented Intelligence has developed new diagnostic tools that use AI to more effectively screen for this condition. Myopic maculopathy occurs when the part of the eye that helps us see straight ahead in sharp detail is stretched and damaged, leading to distorted vision and potentially severe vision loss or blindness.
With experts predicting that myopia will affect approximately 50% of the world’s population by 2050, early intervention is crucial. Wang’s team has created AI algorithms called NN-MobileNet to help software more effectively scan retinal images and predict the correct classification of myopic maculopathy. Their work has been published in the peer-reviewed research journal JAMA Ophthalmology.
The Rise of Myopic Maculopathy: A Growing Concern for Global Health
Myopia, also known as nearsightedness, has been on the rise globally, especially among children. Experts predict that by 2050, myopia will affect approximately 50% of the world’s population. While corrective measures like glasses or contacts can manage the condition for many people, others may develop a more severe and irreversible eye disease called myopic maculopathy.
Myopic maculopathy occurs when the part of the eye responsible for sharp, straight-ahead vision is stretched and damaged, leading to distorted vision. This serious condition is the leading cause of severe vision loss or blindness, with 10 million people affected in 2015. If left unchecked, more than 55 million people are predicted to have vision loss, and approximately 18 million will be blind due to the disease by 2050.
Early Intervention: The Key to Improving Health Outcomes
Catching myopic maculopathy early is crucial for improving health outcomes, especially in children. Ophthalmologists can prescribe special contact lenses or eye drops that slow the progression of the disease. However, diagnosing the condition accurately and efficiently remains a significant challenge.
Currently, myopic maculopathy is diagnosed using optical coherence tomography scans, which are then manually inspected by an ophthalmologist – a time-consuming process requiring specialized expertise. To address this need, researchers have turned to artificial intelligence (AI) and computer-aided screening systems for retinal images.
AI-Powered Solutions: A New Frontier in Medical Imaging
In response to the growing concern of myopic maculopathy, the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society issued a challenge in 2023. Researchers were tasked with improving computer-aided screening systems for retinal images.
One team that answered the call was led by Dr. Yalin Wang from the Geometry Systems Laboratory at Arizona State University. Wang’s team developed new AI algorithms called NN-MobileNet, designed to help software more effectively scan retinal images and predict the correct classification of myopic maculopathy.
The researchers also addressed efforts in the scientific community to use deep neural networks to predict the spherical equivalent in retinal scans. This estimate is crucial for doctors when prescribing glasses or contacts. By developing new algorithms that focused on data quality and relevance, Wang’s team achieved exceptional results while minimizing computing power needs.
Global Health Disparities: A Motivating Force Behind AI-Powered Research
Dr. Yalin Wang explains that one motivating force behind his work is to solve health disparities. “People living in rural areas find it difficult to access sophisticated imaging devices and see physicians,” he says. “Once AI-powered technology becomes available, it will significantly improve the quality of life in worldwide populations, including those who live in developing countries.”
Ross Maciejewski, director of the School of Computing and Augmented Intelligence, notes that Wang’s project is an important example of the excellent work being done by faculty members in the medical space. “With both myopia and myopic maculopathy increasing, solutions are needed to prevent vision loss and help healthcare professionals provide the best treatment options for their patients,” Maciejewski says. “Yalin Wang’s innovative research is a principled use of artificial intelligence to address this dire medical issue.”
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