Systems and methods for processing electronic images

An image processing system, comprising:

• a memory storing instructions;
• and
• a processor configured to execute the instructions to perform operations comprising:
• identifying, using a machine learning system, an area of interest of a target image by analyzing features extracted from image regions in the target image, the machine learning system being generated by processing a plurality of training images each comprising an image of human tissue and a diagnostic label characterizing at least one of a slide morphology, a diagnostic value, and an analytic difficulty;
• determining, using the machine learning system, a probability of a target feature being present in the area of interest of the target image based on an average probability;
• determining, using the machine learning system, a prioritization value, of a plurality of prioritization values, of the target image based on the probability of the target feature being present in the target image, the prioritization value comprising a first prioritization value determined based on preferences of a first user and a second prioritization value determined based on preferences of a second user;
• and
• outputting, using the machine learning system, a sequence of digitized pathology images, wherein a placement of the target image in the sequence is based on the prioritization values.

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform image processing operations, the operations comprising:

• identifying, using a machine learning system, an area of interest of a target image by analyzing features extracted from image regions in the target image, the machine learning system being generated by processing a plurality of training images each comprising an image of human tissue and a diagnostic label characterizing at least one of a diagnostic value, a pathologist review outcome, and an analytic difficulty;
• determining, using the machine learning system, a probability of a target feature being present in the area of interest of the target image based on an average probability;
• determining, using the machine learning system, a prioritization value, of a plurality of prioritization values, of the target image based on the probability of the target feature being present in the target image, the prioritization value comprising a first prioritization value determined based on a first user and a second prioritization value determined based on a second user;
• and
• outputting, using the machine learning system, a sequence of digitized pathology images, wherein a placement of the target image in the sequence is based on the prioritization values.