Medical image identification and interpretation
First Claim
1. A medical image interpretation system, comprising:
- an artificial intelligence findings system that comprises;
an image identification engine that receives new image data pertaining to a patient and past diagnostic reports and past image data pertaining to the patient, the image identification engine using the past image data pertaining to the patient to identify for study, images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data, wherein the image identification engine compensates for incorrect header data accompanying the past image data by analyzing the past image data apart from or in addition to any of the accompanying header data when identifying the images for study, anda findings engine that receives new image data and processes the new image data to generate findings based on the new image data and based on the images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data that are identified for study;
a diagnostic review system that presents the findings to a user, the findings as presented comprising data that includes images; and
,an adjustment engine that receives notifications of changes to findings made by the user when using the medical image interpretation system.
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Accused Products
Abstract
An artificial intelligence findings system includes an artificial intelligence findings system. An image identification engine receives new image data pertaining to a patient and past reports and image data pertaining to the patient. The image identification engine uses the past image data pertaining to the patient to identify for study images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data. A findings engine receives new image data and processes the new image data to generate findings based on the new image data and based on the identified for study images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data. A communication interface provides the findings to a diagnostic review system that presents the findings to a user. An adjustment engine receives notifications of changes to findings made by a user when using the medical image interpretation system.
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Citations
20 Claims
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1. A medical image interpretation system, comprising:
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an artificial intelligence findings system that comprises; an image identification engine that receives new image data pertaining to a patient and past diagnostic reports and past image data pertaining to the patient, the image identification engine using the past image data pertaining to the patient to identify for study, images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data, wherein the image identification engine compensates for incorrect header data accompanying the past image data by analyzing the past image data apart from or in addition to any of the accompanying header data when identifying the images for study, and a findings engine that receives new image data and processes the new image data to generate findings based on the new image data and based on the images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data that are identified for study; a diagnostic review system that presents the findings to a user, the findings as presented comprising data that includes images; and
,an adjustment engine that receives notifications of changes to findings made by the user when using the medical image interpretation system. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method for producing a diagnostic report from medical image data, the method comprising:
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receiving new image data pertaining to a patient and past diagnostic reports and past image data pertaining to the patient; using an image identification engine to identify for study, images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data based on the past image data pertaining to the patient, wherein the image identification engine compensates for incorrect header data accompanying the past image data by analyzing the past image data apart from or in addition to any of the accompanying header data when identifying the images for study; using a findings engine to process the new image data to generate findings based on the new image data and based on the images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data that are identified for study; using a diagnostic review system to present the findings to a user, the findings as presented comprising data that includes images; and
,providing, to an adjustment engine, notifications of changes to findings made by the user when using the medical image interpretation system. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A method for training an artificial intelligence findings system, the method comprising:
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receiving new image data pertaining to a patient and past diagnostic reports and past image data pertaining to the patient; identifying for study, images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data based on the past image data pertaining to the patient, including; compensating for incorrect header data accompanying the past image data by analyzing the past image data apart from or in addition to any of the accompanying header data when identifying the images for study; generating findings based on the new image data and based on the images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data that are identified for study; presenting the findings to a user, the findings as presented comprising data that includes images; and
,tracking findings and adjustments made to the findings by the user to produce tracking information based on the findings and adjustments made to the findings by the user and usage patterns ascertainable based on other users; and receiving the tracking information and based on the tracking information adjusting preferences that are used when identifying for study, the images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data. - View Dependent Claims (20)
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Specification