In Spain, roughly 800,000 people currently suffer from Alzheimer’s disease, and 34% of them are over 85 years of age. These are large numbers due, on the one hand, to the increase in the elderly population in developed countries, and on the other hand, to the fact that it is a disease in which, although it begins many years earlier, the damage to the neurons progresses silently. As for early diagnosis, neurodegenerative diseases begin many years before the first symptoms become evident, and often when we can make a diagnosis, it is already too late. In the end, the earlier the disease is diagnosed, the more effective the treatment will be. The Neuroeye Project has arisen in order to solve this problem.
To research methods of diagnosis using non-invasive techniques
To identify neurodegenerative lesions in the retina
To detect patterns with Deep Learning
Izertis, together with Fernández-Vega Ophthalmological Institute (IOFV) and in collaboration with the Ophthalmic Research Foundation (FIO), is researching a new method for early diagnosis of neurodegenerative diseases such as Alzheimer’s or schizophrenia through observation of the retina. This tissue would be utilized as an accessible part of the central nervous system, since it suffers from the same degenerative processes as cerebral nerve tissue.
The initiative is known as ‘Neuroeye.’ Its goal is to research a non-invasive procedure that enables us to identify neurodegenerative lesions in the retina and in the cornea in order to diagnose diseases such as Alzheimer’s.
In this collaborative project, co-financed by the European Union, Izertis is in charge of the project’s technological section, through analysis of images and detection of patterns using techniques based in Deep Learning. The initiative has been made possible thanks to the ‘training’ of the algorithms to detect, by using the image of the retina, which patients suffer from a neurodegenerative disease.
In this project, different patterns of ocular lesions in patients with Alzheimer’s are studied using optical methods available in all ophthalmology departments in order to differentiate the lesions characteristic of Alzheimer’s disease from other pathologies related with aging, such as macular degeneration or glaucoma. The project utilizes artificial intelligence to compare large quantities of variables. The system is based on algorithms that learn to recognize patterns in optical images of the retina and the cornea. Thanks to this analysis of image and data, we are able to research new early detection systems.