Training set enrichment with insignificantly-abnormal medical images

A system comprising:

• (a) at least one hardware processor;
• and
• (b) a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by said at least one hardware processor to:
• automatically detect, using at least one machine learning algorithm, one or more abnormalities depicted in a medical image of a patient,
• automatically determine whether the one or more abnormalities have remained temporally unchanged, based on an older medical image of the patient, and
• upon determining that the one or more abnormalities have remained temporally unchanged:
• automatically inpaint the one or more abnormalities in the medical image, to enable enrichment of a new training set with the inpainted medical image.

A computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by at least one hardware processor to:

• automatically detect, using at least one machine learning algorithm, one or more abnormalities depicted in a medical image of a patient,
• automatically determine whether the one or more abnormalities have remained temporally unchanged, based on an older medical image of the patient, and
• upon determining that the one or more abnormalities have remained temporally unchanged:
• automatically inpaint the one or more abnormalities in the medical image, to enable enrichment of a new training set with the inpainted medical image.