AI Innovations in Early Detection of Myopic Maculopathy: Protecting Millions from Vision Loss

How AI could protect millions of people from vision loss - Earth.com

Myopia, commonly known as nearsightedness, is increasingly prevalent, especially among children. Experts predict that by 2050, approximately 50% of the world's population will be affected by myopia, which potentially leads to vision loss. Researchers attribute this surge partly to an increase in "near work," which involves focusing on close objects like smartphones and computer screens. While many people manage myopia with glasses or contact lenses, some develop a more severe condition called myopic maculopathy. This condition occurs when the macula - the part of the eye responsible for sharp, central vision - is stretched and damaged due to the elongation of the eyeball into a more football-like shape. The distortion leads to impaired vision and can result in severe vision loss or blindness. In 2015, myopic maculopathy caused visual impairment in 10 million people. If current trends continue, more than 55 million people are expected to experience vision loss due to this condition by 2050, and approximately 18 million people worldwide could become blind from it. Because myopic maculopathy is irreversible, early detection is crucial. Catching the condition in its initial stages can improve health outcomes, especially for children. Ophthalmologists can prescribe special contact lenses or eye drops that slow the disease's progression. A team of researchers at Arizona State University's School of Computing and Augmented Intelligence is developing new diagnostic tools that leverage artificial intelligence (AI) to more effectively screen for myopic maculopathy. Yalin Wang, a professor of computer science and engineering at the university, emphasizes the potential of technology to provide important solutions. "AI is ushering in a revolution that leverages global knowledge to improve diagnosis accuracy, especially in its earliest stage of the disease," he said. "These advancements will reduce medical costs and improve the quality of life for entire societies." In response to this need, the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society issued a challenge in 2023 to improve computer-aided screening systems for retinal images. Currently, myopic maculopathy is diagnosed using optical coherence tomography scans that create detailed images of the retina using reflected light. These scans are often manually inspected by ophthalmologists, which is time-consuming and requires specialized expertise. Professor Wang and his team, including doctoral student Wenhui Zhu and neurologist and adjunct faculty member Dr. Oana Dumitrascu, participated in the MICCAI challenge and were among the winners. For the first part of their work, they classified myopic maculopathy into five categories according to its severity. Accurate classification helps ophthalmologists provide more tailored and effective treatments. The researchers developed new AI algorithms called NN-MobileNet, designed to help software more effectively analyze retinal images and predict the correct classification of myopic maculopathy. Their research was published in the journal Myopic Maculopathy Analysis. Next, the team focused on efforts in the scientific community to use deep neural networks - a type of AI - to predict the spherical equivalent in retinal scans. The spherical equivalent is an estimate of the eye's refractive error, crucial for prescribing corrective lenses. By developing new AI algorithms that emphasized data quality and relevance, they achieved exceptional results while minimizing computing power requirements. This research was also published in Myopic Maculopathy Analysis. Additionally, Professor Wang collaborated with other winning teams from the MICCAI challenge on a third research paper, published in JAMA Ophthalmology in September. The researchers made their findings available to stimulate further advancements in the early and effective diagnosis of myopic maculopathy, aiming to improve health care outcomes globally. Professor Wang explained that one of the driving forces behind his work is addressing health disparities. "People living in rural areas find it difficult to access sophisticated imaging devices and see physicians," he said. "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, praised Wang's project as an important example of innovative work in the medical field. "With both myopia and myopic maculopathy increasing, solutions are needed to prevent vision loss and help health care professionals provide the best treatment options for their patients," said Maciejewski. "Yalin Wang's innovative research is a principled use of artificial intelligence to address this dire medical issue." -- - Like what you read? Subscribe to our newsletter for engaging articles, exclusive content, and the latest updates.

Researchers use AI to help people see more clearly

Myopia, also known as nearsightedness, is on the rise, especially among children. Experts predict that by the year 2050, myopia will affect approximately 50% of the world's population. Researchers believe that an increase in what's called "near work" -- when we interact with close objects like phones and screens -- is partially to blame. For many people, the struggle to see faraway objects is a problem easily managed with glasses or contacts, but for others this develops into a far more serious condition called myopic maculopathy. A team of researchers in the School of Computing and Augmented Intelligence at Arizona State University, is developing new diagnostic tools that use the power of artificial intelligence, or AI, to more effectively screen for this disease. Myopic maculopathy occurs when the part of the eye that helps us see straight ahead in sharp detail is stretched and damaged. Over time, the eye's shape becomes elongated -- more like a football and less like a sphere. When this happens, vision is distorted. This serious condition is the leading cause of severe vision loss or blindness. In 2015, myopic maculopathy resulted in visual impairment in 10 million people. Unless things change, more than 55 million people are predicted to have vision loss and approximately 18 million people worldwide will be blind due to the disease by 2050. Because myopic maculopathy is irreversible, experts want to intervene early. Catching the condition as soon as possible can improve health outcomes, a particularly urgent goal when children are concerned. Ophthalmologists can prescribe special contact lenses or eye drops that slow the progression of the disease. Yalin Wang, a Fulton Schools professor of computer science and engineering, says innovations in technology can provide important solutions. "AI is ushering in a revolution that leverages global knowledge to improve diagnosis accuracy, especially in its earliest stage of the disease," he says. "These advancements will reduce medical costs and improve the quality of life for entire societies." A challenge to see things in a new way In response to this need, the Medical Image Computing and Computer Assisted Intervention, or MICCAI, Society issued a challenge in 2023. The professional organization that seeks to drive innovation in biomedical research asked experts to improve computer-aided screening systems for retinal images. Currently, myopic maculopathy is diagnosed using optical coherence tomography scans that use reflected light to create pictures of the back of the eye. These scans are then often manually inspected by an ophthalmologist, a time-consuming process that can require specialized experience. Wang and his team in the Geometry Systems Laboratory answered the call. The researchers were one of the winners of the MICCAI challenge. For the first part of the work, Wang and his team -- which includes computer engineering doctoral student Wenhui Zhu as well as neurologist and Fulton Schools adjunct faculty member Dr. Oana Dumitrascu -- addressed the classification of myopic maculopathy. The disease has five classifications that describe its severity. Determining the correct level helps ophthalmologists to provide more tailored, effective solutions to the patient. The Fulton Schools researchers created new AI algorithms called NN-MobileNet. These sets of instructions that computer programs follow to do their work are designed to help software more effectively scan retinal images and predict the correct classification of myopic maculopathy. The research was published in Myopic Maculopathy Analysis. Next, the team turned their attention to efforts in the scientific community to use a type of AI called deep neural networks to predict the spherical equivalent in retinal scans. The spherical equivalent is an estimate of the eye's refractive error that doctors need when prescribing glasses or contacts. In deep neural networks, researchers task computers with analyzing huge sets of data and apply AI-powered algorithms to draw helpful conclusions. With a more accurate measure of the spherical equivalent, doctors can make more accurate treatment recommendations. So, Wang and the team again developed new algorithms that focused on data quality and relevance. Their new model of retinal image analysis achieved exceptional results while minimizing the amount of computing power needed. The results of this research were also published in Myopic Maculopathy Analysis. Finally, Wang collaborated with other winning teams from the MICCAI challenge on a third research paper, published in JAMA Ophthalmology in September, that presented their collected results. The researchers from universities around the world made their challenge findings available to stimulate additional advancements and discoveries in the early and effective diagnosis of myopic maculopathy and improving health care outcomes for people across the globe. A better vision for global health 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, says 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 health care 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."

Researchers use AI to help people see more clearly

Myopia, also known as nearsightedness, is on the rise, especially among children. Experts predict that by the year 2050, myopia will affect approximately 50% of the world's population. Researchers believe that an increase in what's called "near work" -- when we interact with close objects like phones and screens -- is partially to blame. For many people, the struggle to see faraway objects is a problem easily managed with glasses or contacts, but for others this develops into a far more serious condition called myopic maculopathy. A team of researchers in the School of Computing and Augmented Intelligence at Arizona State University, is developing new diagnostic tools that use the power of artificial intelligence, or AI, to more effectively screen for this disease. They have recently published the results of their work in the peer-reviewed research journal JAMA Ophthalmology. Myopic maculopathy occurs when the part of the eye that helps us see straight ahead in sharp detail is stretched and damaged. Over time, the eye's shape becomes elongated -- more like a football and less like a sphere. When this happens, vision is distorted. This serious condition is the leading cause of severe vision loss or blindness. In 2015, myopic maculopathy resulted in visual impairment in 10 million people. Unless things change, more than 55 million people are predicted to have vision loss and approximately 18 million people worldwide will be blind due to the disease by 2050. Because myopic maculopathy is irreversible, experts want to intervene early. Catching the condition as soon as possible can improve health outcomes, a particularly urgent goal when children are concerned. Ophthalmologists can prescribe special contact lenses or eye drops that slow the progression of the disease. Yalin Wang, a Fulton Schools professor of computer science and engineering, says innovations in technology can provide important solutions. "AI is ushering in a revolution that leverages global knowledge to improves diagnosis accuracy, especially in its earliest stage of the disease," he says. "These advancements will reduce medical costs and improve the quality of life for entire societies." A challenge to see things in a new way In response to this need, the Medical Image Computing and Computer Assisted Intervention, or MICCAI, Society issued a challenge in 2023. The professional organization that seeks to drive innovation in biomedical research asked experts to improve computer-aided screening systems for retinal images. Currently, myopic maculopathy is diagnosed using optical coherence tomography scans that use reflected light to create pictures of the back of the eye. These scans are then often manually inspected by an ophthalmologist, a time-consuming process that can require specialized experience. Wang and his team in the Geometry Systems Laboratory answered the call. The researchers were one of the winners of the MICCAI challenge. For the first part of the work, Wang and his team -- which includes computer engineering doctoral student Wenhui Zhu as well as neurologist and Fulton Schools adjunct faculty member Dr. Oana Dumitrascu -- addressed the classification of myopic maculopathy. The disease has five classifications that describe its severity. Determining the correct level helps ophthalmologists to provide more tailored, effective solutions to the patient. The Fulton Schools researchers created new AI algorithms called NN-MobileNet. These sets of instructions that computer programs follow to do their work are designed to help software more effectively scan retinal images and predict the correct classification of the myopic maculopathy. Next, the team turned their attention to efforts in the scientific community to use a type of AI called deep neural networks to predict the spherical equivalent in retinal scans. The spherical equivalent is an estimate of the eye's refractive error that doctors need when prescribing glasses or contacts. In deep neural networks, researchers task computers with analyzing huge sets of data and apply AI-powered algorithms to draw helpful conclusions. With a more accurate measure of the spherical equivalent, doctors can make more accurate treatment recommendations. So, Wang and the team again developed new algorithms that focused on data quality and relevance. Their new model of retinal image analysis achieved exceptional results while minimizing the amount of computing power needed. The results of this research were also published in JAMA Ophthalmology. Finally, Wang collaborated with other winning teams from the MICCAI challenge on a third research paper, published in JAMA Ophthalmology in September, that presented their collected results. The researchers from universities around the world made their challenge findings available to stimulate additional advancements and discoveries in the early and effective diagnosis of myopic maculopathy and improving health care outcomes for people across the globe. A better vision for global health 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, says 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 health care 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."

Researchers use AI to help people see more clearly | Newswise

Professor Yalin Wang at work in his office. The researcher in the School of Computing and Augmented Intelligence and his team have published a series of papers in the peer-reviewed research journal JAMA Ophthalmology that outline their innovative projects. Myopia, also known as nearsightedness, is on the rise, especially among children. Experts predict that by the year 2050, myopia will affect approximately 50% of the world's population. Researchers believe that an increase in what's called "near work" -- when we interact with close objects like phones and screens -- is partially to blame. For many people, the struggle to see faraway objects is a problem easily managed with glasses or contacts, but for others this develops into a far more serious condition called myopic maculopathy. A team of researchers in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at Arizona State University, is developing new diagnostic tools that use the power of artificial intelligence, or AI, to more effectively screen for this disease. They have recently published the results of their work in the peer-reviewed research journal JAMA Ophthalmology. Myopic maculopathy occurs when the part of the eye that helps us see straight ahead in sharp detail is stretched and damaged. Over time, the eye's shape becomes elongated -- more like a football and less like a sphere. When this happens, vision is distorted. This serious condition is the leading cause of severe vision loss or blindness. In 2015, myopic maculopathy resulted in visual impairment in 10 million people. Unless things change, more than 55 million people are predicted to have vision loss and approximately 18 million people worldwide will be blind due to the disease by 2050. Because myopic maculopathy is irreversible, experts want to intervene early. Catching the condition as soon as possible can improve health outcomes, a particularly urgent goal when children are concerned. Ophthalmologists can prescribe special contact lenses or eye drops that slow the progression of the disease. Yalin Wang, a Fulton Schools professor of computer science and engineering, says innovations in technology can provide important solutions. "AI is ushering in a revolution that leverages global knowledge to improves diagnosis accuracy, especially in its earliest stage of the disease," he says. "These advancements will reduce medical costs and improve the quality of life for entire societies." In response to this need, the Medical Image Computing and Computer Assisted Intervention, or MICCAI, Society issued a challenge in 2023. The professional organization that seeks to drive innovation in biomedical research asked experts to improve computer-aided screening systems for retinal images. Currently, myopic maculopathy is diagnosed using optical coherence tomography scans that use reflected light to create pictures of the back of the eye. These scans are then often manually inspected by an ophthalmologist, a time-consuming process that can require specialized experience. Wang and his team in the Geometry Systems Laboratory answered the call. The researchers were one of the winners of the MICCAI challenge. For the first part of the work, Wang and his team -- which includes computer engineering doctoral student Wenhui Zhu as well as neurologist and Fulton Schools adjunct faculty member Dr. Oana Dumitrascu -- addressed the classification of myopic maculopathy. The disease has five classifications that describe its severity. Determining the correct level helps ophthalmologists to provide more tailored, effective solutions to the patient. The Fulton Schools researchers created new AI algorithms called NN-MobileNet. These sets of instructions that computer programs follow to do their work are designed to help software more effectively scan retinal images and predict the correct classification of the myopic maculopathy. Next, the team turned their attention to efforts in the scientific community to use a type of AI called deep neural networks to predict the spherical equivalent in retinal scans. The spherical equivalent is an estimate of the eye's refractive error that doctors need when prescribing glasses or contacts. In deep neural networks, researchers task computers with analyzing huge sets of data and apply AI-powered algorithms to draw helpful conclusions. With a more accurate measure of the spherical equivalent, doctors can make more accurate treatment recommendations. So, Wang and the team again developed new algorithms that focused on data quality and relevance. Their new model of retinal image analysis achieved exceptional results while minimizing the amount of computing power needed. The results of this research were also published in JAMA Ophthalmology. Finally, Wang collaborated with other winning teams from the MICCAI challenge on a third research paper, published in JAMA Ophthalmology in September, that presented their collected results. The researchers from universities around the world made their challenge findings available to stimulate additional advancements and discoveries in the early and effective diagnosis of myopic maculopathy and improving health care outcomes for people across the globe. 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, says 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 health care 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."

Using advanced AI screening tools to improve early detection of myopic maculopathy

Arizona State UniversityOct 3 2024 Myopia, also known as nearsightedness, is on the rise, especially among children. Experts predict that by the year 2050, myopia will affect approximately 50% of the world's population. Researchers believe that an increase in what's called "near work" -; when we interact with close objects like phones and screens -; is partially to blame. For many people, the struggle to see faraway objects is a problem easily managed with glasses or contacts, but for others this develops into a far more serious condition called myopic maculopathy. A team of researchers in the School of Computing and Augmented Intelligence at Arizona State University, is developing new diagnostic tools that use the power of artificial intelligence, or AI, to more effectively screen for this disease. They have recently published the results of their work in the peer-reviewed research journal JAMA Ophthalmology. Myopic maculopathy occurs when the part of the eye that helps us see straight ahead in sharp detail is stretched and damaged. Over time, the eye's shape becomes elongated -; more like a football and less like a sphere. When this happens, vision is distorted. This serious condition is the leading cause of severe vision loss or blindness. In 2015, myopic maculopathy resulted in visual impairment in 10 million people. Unless things change, more than 55 million people are predicted to have vision loss and approximately 18 million people worldwide will be blind due to the disease by 2050. Because myopic maculopathy is irreversible, experts want to intervene early. Catching the condition as soon as possible can improve health outcomes, a particularly urgent goal when children are concerned. Ophthalmologists can prescribe special contact lenses or eye drops that slow the progression of the disease. Yalin Wang, a Fulton Schools professor of computer science and engineering, says innovations in technology can provide important solutions. AI is ushering in a revolution that leverages global knowledge to improves diagnosis accuracy, especially in its earliest stage of the disease. These advancements will reduce medical costs and improve the quality of life for entire societies." Yalin Wang, a Fulton Schools professor of computer science and engineering A challenge to see things in a new way In response to this need, the Medical Image Computing and Computer Assisted Intervention, or MICCAI, Society issued a challenge in 2023. The professional organization that seeks to drive innovation in biomedical research asked experts to improve computer-aided screening systems for retinal images. Currently, myopic maculopathy is diagnosed using optical coherence tomography scans that use reflected light to create pictures of the back of the eye. These scans are then often manually inspected by an ophthalmologist, a time-consuming process that can require specialized experience. Wang and his team in the Geometry Systems Laboratory answered the call. The researchers were one of the winners of the MICCAI challenge. For the first part of the work, Wang and his team -; which includes computer engineering doctoral student Wenhui Zhu as well as neurologist and Fulton Schools adjunct faculty member Dr. Oana Dumitrascu -; addressed the classification of myopic maculopathy. The disease has five classifications that describe its severity. Determining the correct level helps ophthalmologists to provide more tailored, effective solutions to the patient. The Fulton Schools researchers created new AI algorithms called NN-MobileNet. These sets of instructions that computer programs follow to do their work are designed to help software more effectively scan retinal images and predict the correct classification of the myopic maculopathy. Next, the team turned their attention to efforts in the scientific community to use a type of AI called deep neural networks to predict the spherical equivalent in retinal scans. The spherical equivalent is an estimate of the eye's refractive error that doctors need when prescribing glasses or contacts. In deep neural networks, researchers task computers with analyzing huge sets of data and apply AI-powered algorithms to draw helpful conclusions. With a more accurate measure of the spherical equivalent, doctors can make more accurate treatment recommendations. So, Wang and the team again developed new algorithms that focused on data quality and relevance. Their new model of retinal image analysis achieved exceptional results while minimizing the amount of computing power needed. The results of this research were also published in JAMA Ophthalmology. Finally, Wang collaborated with other winning teams from the MICCAI challenge on a third research paper, published in JAMA Ophthalmology in September, that presented their collected results. The researchers from universities around the world made their challenge findings available to stimulate additional advancements and discoveries in the early and effective diagnosis of myopic maculopathy and improving health care outcomes for people across the globe. A better vision for global health 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, says 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 health care 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." Arizona State University Journal reference: Qian, B., et al. (2024). A Competition for the Diagnosis of Myopic Maculopathy by Artificial Intelligence Algorithms. JAMA Ophthalmology. doi.org/10.1001/jamaophthalmol.2024.3707.