Аннтотация

© 2018 The Author(s). The article describes the processes of collecting and adapting the diagnostic information necessary for use in automated analysis of three-dimensional images and surgical navigation. The work is carried out on the basis of the NMRC Obstetrics, Gynecology And Perinatology named after V.I. Kulakov of the Ministry of Health of the Russian Federation with the financial support of the Ministry of Science and Education of the Russian Federation (Agreement dated 03.10.2016 No. 14.607.21.0162, unique identifier RFMEFI60716X0162) The work is devoted to the features of collection, segmentation and description of the results of preoperative radiological diagnostics of newborn patients with congenital urinary malformations such as hydronephrosis (HN), renal duplication with uretherohydronephrosis of the nonfunctional segment (UHN) or multicystic dysplastic kidney (MC). The goal of the work is the development of standards for the collection, classification and segmentation of various diagnostic information of congenital urinary malformations in newborns necessary to use in automated three-dimensional image analysis and surgical navigation. In order to expand the scope of application, it was decided to supplement the data bank with information from the patient's phenotypic chart, compiled by the clinical geneticist when examining the patient. According to the developed and implemented algorithms we collected and segmented 978 series of images belonging to 393 patients with urinary malformations and 452 series of normal urinary System. Available text descriptions of the series are reconstructed to the original developed standard. At present, using this data bank, a subSystem of neural network analysis and reconstruction of diagnostic images of newborn patients is being developed, as well as a surgical navigation System for performing endoscopic surgical manipulations on patients for congenital malformations of the urinal System.