V.N. Gridin – Dr. Sc. (Eng.), Professor, Scientific Director of the Design Information Technologies Center (Odintsovo, Moscow Region)
E.S. Sirota – Dr. Sc. (Med.), Leading Research Scientist, Design Information Technologies Center (Odintsovo, Moscow region); I.M. Sechenov First Moscow State Medical University
M.I. Trufanov – Ph.D. (Eng.), Associate Professor, Head of Laboratory, Design Information Technologies Center (Odintsovo, Moscow region)
V.S. Panishchev – Ph.D. (Eng.), Senior Research Scientist, Design Information Technologies Center, (Odintsovo, Moscow region)
Estimation the quantitative characteristics of the spread of contrast medium during various phases of the study of the abdominal cavity is important task in the field of data processing of multi-spiral computed tomography. To solve the problem of determining the area of distribution of the contrast medium, manual measurement of the area of the contrast medium for various phases is used, which requires the presence of certain experience with the doctor and reduces the effectiveness of its practical application and may introduce potential errors. Purpose. The goal is to produce algorithm for automatic estimation the area of a contrast medium for different phases of contrast medium circulation. Results. An image processing algorithm is proposed for assessing the degree of distribution of contrast medium in the study of abdominal organs, including normalizing images and reducing noise through the use of a Gaussian filter, calculating image characteristics, image segmentation, assessing the position of the contrast medium taking into account their distribution in the kidney in different phases of the study. Next, the total number of pixels belonging to the contrast medium is determined in the image for each optical section, after which the integral score is determined, which is then used by the doctor to construct images of the abdominal organs.A distinctive novelty of the proposed method is the solution of the problem of comparing the patient’s location at different phases of contrast medium distribution by isolating the spinal column and linking the patient’s images to the spinal column. Experimental studies were conducted on a series of images of several patients (an average of 1600 images were analyzed for each patient), confirming the possibility of using the developed approach.
Practical significance. The results obtained allow automatic analysis of sequential tomographic images in order to form a nu-merical estimate of the degree of distribution of contrast medium in the study of kidneys and other organs and systems in the abdominal cavity.
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