Alzheimer's disease - a common neurodegenerative disease in the elderly. Early diagnosis is critical for treatment and the search for new medicines. The development of Alzheimer's disease is associated with structural changes in the gray matter and functional changes in the white matter that connect brain regions. The cord connecting net loss of white matter causes such functional changes as memory loss. However, it is difficult to determine how brain activity contributes to the deterioration of the structural activity, and vice versa.
Computer diagnostics - an important tool that helps doctors understand the contents of the tests and to simplify the processing. One of these procedures is medical imaging, which provides high resolution "live" information. BioSip research team from the University of Malaga, in collaboration with scientists from the University of Granada studied biomedical images and signals for several years.
It is published an Researchers of The article in the International,, the Journal Of the Neural Systems '' . The paper presents a method of deep study diagnosis of Alzheimer's disease via a joint analysis of the structural and functional images.
Artificial Intelligence techniques (AI) is aimed at modeling data to computers differentiated brain of a healthy person of the patient by automatically extracting the affected areas of interest. Scientists have used a variety of neural networks, which can be modeled by each area of the brain to combine them in the future.
The study examines the methods based on educational models used in areas of the brain, called the automatic anatomical labeling. Images of the gray matter of the brain of each area divided into sectors for the study of neural networks. The data obtained from the network, then combined synthesis method presented in the article.
The result is a classification of models for automatically extracting the most relevant features of a set of images. The proposed method estimated using a database derived from a group neuroimaging Alzheimer's Disease (ADNI).
The results of the work, which included data of patients with other cognitive impairment, which can develop into with Alzheimer's over time, show the potential of artificial intelligence techniques to identify patterns associated with the disease. data accuracy achieved in the diagnosis, helps to better understand neurodegenerative processes involved in the development of the disease, and to develop more effective treatments.