METHOD FOR DETECTING ONCOLOGICAL DISEASES IN PELVIC ORGANS AND SYSTEM FOR IMPLEMENTING METHOD Russian patent published in 2024 - IPC G16H30/20 G16H30/40 G16H50/20 G06V10/20 G06N3/02 

FIELD: medicine; image processing.

SUBSTANCE: invention relates to processing and analysis of medical images, including MRI of pelvic organs. Method comprises obtaining MRI images of the pelvic organs in the format of a set of DICOM files, first stage of processing MRI images, which is carried out on local device of a medical institution with subsequent direction to the second stage of MRI images processing, which is carried out on a device for determining pathology — a remote server, using artificial intelligence algorithms and machine learning models, based on the results of which a conclusion is made on the presence or absence of a lesser pelvic involvement, after which the processing results are returned to the local device of the medical institution. At the first stage of MRI image processing: a) selecting series of images in axial or oblique axial projection, including series of T2-weighted images, b) performing anonymisation of selected series by deleting personal data from each image of each series with subsequent assignment to each image of a temporary unique identifier (ID), c) performing anatomical synchronization of images from the selected series by spatially combining each image from the T2-weighted series with corresponding or closest to it image from other series using metadata of DICOM files and/or anatomical landmarks, d) forming a queue of images obtained at steps b) and c) with subsequent transmission of all images in form of one packet to a remote server, at the second stage of processing MRI images: e) receiving the generated packets from the queue and storing them in the object storage unit in the folder under the obtained unique ID with simultaneous transmission of links from caching queue unit, from which images obtained at step c) are transmitted for parallel asynchronous processing by machine learning models, f) wherein the images obtained from the queue are processed in the following sequence: first, synchronized images are processed with a machine learning model configured to pre-classify the target pelvic organ, then, are processed with at least one binary classification model trained to detect the presence of a malignant neoplasm of the target pelvic organ, also two segmentation models and one detection model with provision of complex image analysis and graphic representation of area with pathological changes; conclusion on the presence or absence of a malignant neoplasm of the target pelvic organ is made when the results of image processing by the binary classification model and the segmentation and detection models match; obtained results of the second stage of image processing are a plurality of masks in the form of a set of images of segments of anatomical regions and regions with pathological changes containing coordinates and the stored dimension of the source image from the server of the medical institution.

EFFECT: more accurate detection of pelvic cancer.

29 cl, 12 dwg