V.N. Gridin – Dr. Sc. (Eng.), Professor, Head of Researches, Design Information Technologies  Center of RAS (Odintsovo, Moscow Region)

E-mail: info@ditc.ras.ru

V.A. Perepelov – Research Engineer, Design Information Technologies Center of RAS  (Odintsovo, Moscow Region); I.M. Sechenov First Moscow State Medical University

E-mail: info@ditc.ras.ru

V.S. Panishchev – Ph.D., Senior Research Scientist, Design Information Technologies Center of RAS  (Odintsovo, Moscow Region) 

E-mail: info@ditc.ras.ru

M.I. Truphanov – Ph.D. (Eng.), Associate Professor, Head of Laboratory, Design Information Technologies  Center of RAS (Odintsovo, Moscow Region)

E-mail: info@ditc.ras.ru

N.N. Yakhno – Academician of RAS, Dr Sc. (Med.), Professor, I.M. Sechenov First Moscow State Medical  University; Chief Research Scientist, Design Information Technologies Center Russian Academy of Sciences (Odintsovo, Moscow Region)

E-mail: info@ditc.ras.ru  

The article goals to the problem of analyzing the volumetric characteristics of the hippocampus in the context of detection of MRI images of Alzheimer's disease. One of the key tasks in the study of cognitive impairment is the analysis of the volumetric characteristics of the hippocampus, as the main structure used to detect Alzheimer's disease by MRI. The goal of the work is to create algorithms and software for calculating the parameters of the hippocampus in the diagnosis of Alzheimer's disease. During solving the problem, the analysis of existing works was maked. This analisys has approved that calculating of parameters of the hippocampus is important to make without using a priori generalized information from different medical atlases. An algorithm for detecting the hippocampus on a common series of images obtained by a magnetic resonance imager was developed. The proposed algorithm includes the following main blocks: preliminary data input and evaluation of processing parameters; calculation of ordinal indices of key images obtained in the sagittal projection; construction of segments on each image corresponding to different structures of the brain; determination of the boundaries of intracranial fluid located above the hippocampus; determination of the position of the hippocampus; assessment of the volume of the hippocampus relative to the total volume of the brain; issuance of processing results to decide on the presence or absence of Alzheimer's disease. The results of simulation of the developed algorithm are presented. The algorithm allows without using a priori information to perform an analysis of the magnetic resonance images of the brain and determine the position of the hippocampus and to measure its relative volume. Distinctive features of the developed algorithm are: reduced volume of processed images due to preliminary sampling of key images, presumably containing the hippocampus; the absence of the need to use atlases with a priori given generalized parameters and the location of the hippocampus, which ensures the correct processing and search of the hippocampus for patients with Alzheimer's disease and for healthy people; the ability to process data without using significant amounts of memory computing resources due to the phased allocation of key data, processing only informative images and step-bystep loading and image analysis; the ability to calculate the relative total brain volume of the hippocampus. The created approach can be applied in solving a wide range of problems related to the analysis of key brain structures in the practice of applied medical and fundamental scientific research of cognitive impairment.

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