FIELD: medical science.
SUBSTANCE: invention relates to medicine, specifically to processing and examination of medical images. Method includes a step of selecting images from a source DICOM image packet of a target organ of a patient; preprocessing the loaded images, resulting in single 3D image of the region of interest; image analysis using an algorithm based on neural networks, at the stage of which image packets are formed, which are further supplied to a pre-trained U-Net-like network for segmenting pathologies and a U-net-like network for segmenting kidney segments to obtain masks of probabilities for classes of pathologies, after which the obtained probabilities masks are combined to produce averaged 3D mask of the probabilities of pathology classes and 3D mask of the anatomical zones of the kidneys; postprocessing, at the stage of which, based on the obtained masks using clustering and classification algorithms, the anatomical localization of limiting surfaces is determined.
EFFECT: high-accuracy detection of kidney formations based on the analysis results of images obtained both with the introduction, and without the introduction of a contrast agent, as well as automatic measurement of their characteristics.
20 cl, 11 dwg, 1 tbl
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Authors
Dates
2025-05-05—Published
2024-12-29—Filed