IMPLICIT REGISTRATION FOR IMPROVING SYNTHESIZED FULL-CONTRAST IMAGE PREDICTION TOOL

• Main Authors: CORONA, Veronica, LORIO, Sara, PURTORAB, Marvin, RAMOS DOS SANTOS, Thiago
• Format: Patent
• Language: English
• Published: 13.06.2024
• Subjects: CALCULATING; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS

A method of training a prediction tool to generate at least one synthetic full-contrast image from zero-contrast and low-contrast images of a subject may involve receiving a training set a set of images of a set of subjects, the images of each subject comprising a full-contrast image, a low-contrast image, a first zero-contrast image acquired prior to the acquisition of the full-contrast image, and a second zero-contrast image acquired prior to the acquisition of the low-contrast image. An artificial neural network may be trained with the training set by applying the first and second zero-contrast images from the set of images and the low-contrast images from the set of images as input to the artificial neural network and using a cost function to compare the output of the artificial neural network with the full-contrast images from the set of images to train parameters of the artificial neural network using backpropagation.