Learning-based domain transformation for medical images

A computer-implemented method, comprising:

• accessing, by a device operatively coupled to a processor, a medical image, wherein the medical image depicts an anatomical structure according to a first medical scanning domain;
• identifying, by the device and via execution of a segmentation model, a region-of-interest in the medical image;
• and
• generating, by the device and via execution of a machine learning model, a predicted image based on the medical image, wherein the predicted image depicts the anatomical structure according to a second medical scanning domain that is different from the first medical scanning domain, and wherein the machine learning model is executed on the region-of-interest and not on a remainder of the medical image.

A computer program product for facilitating learning-based domain transformation for medical images, the computer program product comprising a computer-readable memory having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

• access a medical image, wherein the medical image depicts an anatomical structure according to a first medical scanning domain;
• identify, via execution of a segmentation model, a region-of-interest in the medical image;
• and
• generate, via execution of a machine learning model, a predicted image based on the medical image, wherein the predicted image depicts the anatomical structure according to a second medical scanning domain that is different from the first medical scanning domain, and wherein the machine learning model is executed on the region-of-interest and not on a remainder of the medical image.