Systems and methods for processing images for image matching
AssigneePaige.AI, Inc.
InventorsChristopher Kanan, Leo Grady
Life of this patent
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Abstract
A computer-implemented method for processing electronic medical images, the method including receiving a plurality of electronic medical images of a medical specimen associated with a single patient. The plurality of electronic medical images may be inputted into to a trained machine learning system, the trained machine learning system being trained to compare each of the plurality of electronic medical images to each other to determine whether each pair of the electronic medical images matches within a predetermined similarity threshold. The trained machine learning system may output whether each pair of the electronic medical images matches within a predetermined similarity threshold. The output may be stored.
Claims18
A computer-implemented method for processing electronic medical images, comprising:
- receiving a plurality of electronic medical images associated with a medical sample of a first patient;
- providing the plurality of electronic medical images to a trained machine learning system, the trained machine learning system being trained with vectors extracted from each of the plurality of electronic medical images, the vectors concatenated to form unified vectors for each of the plurality of electronic medical images, wherein the trained machine learning system compares each of the plurality of electronic medical images to each other to determine whether each pair of the electronic medical images matches within a predetermined similarity threshold based on the training;
- receiving, from the trained machine learning system, an output indicating whether each pair of the plurality of electronic medical images matches within the predetermined similarity threshold, wherein a match within the predetermined similarity threshold indicates that a pair of electronic medical images is associated with the medical sample of the first patient;
- and
- outputting and/or storing the output indicating whether each pair of the electronic medical images matches within the predetermined similarity threshold.
A system for processing electronic digital medical images, the system comprising:
- at least one memory storing instructions;
- and
- at least one processor configured to execute the instructions to perform operations comprising:
- receiving a plurality of electronic medical images associated with a medical sample of a first patient;
- providing the plurality of electronic medical images to a trained machine learning system, the trained machine learning system being trained with vectors extracted from each of the plurality of electronic medical images, the vectors concatenated to form unified vectors for each of the plurality of electronic medical images, wherein the trained machine learning system compares each of the plurality of electronic medical images to each other to determine whether each pair of the electronic medical images matches within a predetermined similarity threshold based on the training;
- receiving, from the trained machine learning system, an output indicating whether each pair of the plurality of electronic medical images matches within the predetermined similarity threshold, wherein a match within the predetermined similarity threshold indicates that a pair of electronic medical images is associated with the medical sample of the first patient;
- and
- outputting and/or storing the output indicating whether each pair of the electronic medical images matches within the predetermined similarity threshold.
A non-transitory computer-readable medium storing instructions that, when executed by a processor, perform operations processing electronic digital medical images, the operations comprising:
- receiving a plurality of electronic medical images associated with a medical sample of a first patient;
- providing the plurality of electronic medical images to a trained machine learning system, the trained machine learning system being trained with vectors extracted from each of the plurality of electronic medical images, the vectors concatenated to form unified vectors for each of the plurality of electronic medical images, wherein the trained machine learning system compares each of the plurality of electronic medical images to each other to determine whether each pair of the electronic medical images matches within a predetermined similarity threshold based on the training;
- receiving, from the trained machine learning system, an output indicating whether each pair of the plurality of electronic medical images matches within the predetermined similarity threshold, wherein a match within the predetermined similarity threshold indicates that a pair of electronic medical images is associated with the medical sample of the first patient;
- and
- outputting and/or storing the output indicating whether each pair of the electronic medical images matches within the predetermined similarity threshold.
Dependencies are inferred from the claim text.