Abstract: Disclosed is a medical image conversion method and apparatus. The medical image conversion apparatus trains a first artificial intelligence model to output a second contrast-enhanced image, based on first learning data including a pair of a first contrast-enhanced image and a first non-contrast image, and trains a second artificial intelligence model to output a second non-contrast image, based on second learning data including a pair of the first non-contrast image of the first learning data and the second contrast-enhanced image. The disclosure was supported by the “AI Precision Medical Solution (Doctor Answer 2.0) Development” project hosted by Seoul National University Bundang Hospital (Project Serial No.: 1711151151, Project No.: S0252-21-1001).

Abstract: A method and a device for converting a non-contrast image into a contrast image are disclosed. The image conversion device converts the non-contrast image into the contrast image by using a deep learning network trained with learning data including one or more contrast learning images and one or more non-contrast learning images. The disclosure was supported by the “Critical Care Patient Specialized Big Data Construction and AI-based CDSS Development” project hosted by Seoul National University Hospital (Task identification number: HI21C1074, Assignment number: HI21C1074050021).