METHOD OF TRAINING A CONVOLUTION NEURAL NETWORK TO CARRY OUT TELEROENTGENOGRAM MARKINGS IN A DIRECT AND LATERAL PROJECTIONS Russian patent published in 2020 - IPC G06N3/08 

FIELD: computer equipment.

SUBSTANCE: invention relates to computer engineering and medicine. Method comprises steps of: creating a database (DB) with pre-analyzed and marked cephalometric points and their coordinates on teleroentgenograms in direct and lateral projections (TRGD and TRGL); based on the prepared DB, training at least one convolutional neural network (CNN) is marked with cephalometric points of the teleroentgenograms in the direct and lateral projections (TRGD and TRGL), wherein: the CNN input is fed with images from the DB, with points N marked thereon, and multilayer mask M for said points; CNN analyzes multilayer masks M and places them on N masks M_1 …M_N by number of marked points on input images; finding connectivity components for each layer of masks, wherein each component is predicted coordinates of points on images position; comparing predicted coordinates with coordinates of marked points on input images from DB and calculating root-mean-square deviation; trained at least one CNN is used for further marking with cephalometric points of teleroentgenogram in direct and lateral projections.

EFFECT: provision for training of a convolution neural network to carry out marking of teleroentgenograms in direct and lateral projections.

5 cl, 2 dwg