Systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking
The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.
1. An apparatus for generating and displaying a medical report for a patient, the medical report associated with one or more tests of the patient and based on medical images including one or more images from a set of images generated non-invasively of the patient, comprising:
a non-transitory computer readable storage medium configured to store executable instructions; and
one or more hardware processors in communication with the computer readable storage medium, wherein the executable instructions, when executed by the one or more processors, configure the one or more processors to:
receive a medical report generation request, the medical report generation request indicating a particular patient and type of medical report;
retrieve from a database, patient information associated with the patient indicated in the medical report generation request, the patient information comprising characteristics associated with the patient including age, gender, and language of the patient;
retrieve, from a database, patient medical information associated with the patient indicated in the medical report generation request based on the type of medical report indicated in the medical report generation request, wherein the patient medical information includes
test results of one or more test performed on the patient,
one or more medical images depicting target features of the patient's body, the one or more images including one or more computed tomography (CT) images from a set of CT images,
measurements of lumen, vessel walls, plaque of coronary vessels, and visualizations of vessels of the patient including a straightened multiplanar reformat (SMPR) vessel view depicting areas of good and/or bad plaque, determined automatically based at least in part by applying a machine learning algorithm to the one or more CT images, and;
retrieve from a database, report content associated with the patient information and the type of medical report, the report content comprising
multimedia content that is associated with the patient information but not related to a specific patient, the multimedia content including
a greeting segment in the language of the patient,
an explanation segment in the language of the patient explaining a type of test conducted,
a results segment in the language of the patient for presenting the test results and analysis performed on the patient, the test results and analysis including the one or more of the measurements of the lumen, vessel walls, and/or plaque of coronary arteries, and further including the visualizations of vessels of the patient including the straightened multiplanar reformat (SMPR) vessel view depicting areas of good and/or bad plaque,
an explanation segment in the language of the patient explaining the test results, and
a conclusion segment in the language of the patient; and
generate, using the retrieved patient information, patient medical information, and report content, a medical report configured to presented on a computer display, the medical report including, in the language of the patient, a greeting, an explanation of the type of test conducted, the test results and analysis preformed on the patient, and a conclusion.
2. The apparatus of claim 1 , wherein one or more of the CT images are generated non-invasively using a normalization device, wherein the normalization device improves accuracy of the non-invasive medical image analysis.
3. The apparatus of claim 1 , wherein the one or more medical images include one or more magnetic resonance imaging (MM) images from a set of MM images generated non-invasively using a normalization device, wherein the normalization device improves accuracy of the non-invasive medical image analysis, and wherein patient's medical information comprises measurements of the target features determined from the one or more MM images by image processing images rendered from the set of MRI images.
4. The apparatus of claim 1 , wherein the one or more medical images include one or more ultrasound images from a set of ultrasound images generated non-invasively using a normalization device, wherein the normalization device improves accuracy of the non-invasive medical image analysis, and wherein patient's medical information comprises measurements of the target features determined from the one or more ultrasound images by image processing images rendered from the set of ultrasound images.
5. The apparatus of claim 1 , wherein the executable instructions, when executed by the one or more processors, further configure the one or more processors to display the medical report in a user interface on a computer display.
6. The apparatus of claim 5 , wherein the computer display is on a smart phone, a laptop computer, a tablet computer, or a desktop computer.
7. The apparatus of claim 5 , wherein the report content further comprises information for including an avatar in the medical report and displaying the avatar in the user interface when the medical report is displayed.
8. The apparatus of claim 7 , wherein the avatar is based on the one or more patient characteristics.
9. The apparatus of claim 7 , wherein the avatar is based on one or more of age, race, or gender of the patient.
10. The apparatus of claim 1 , wherein the executable instructions, when executed by the one or more processors, further configure the one or more processors to access one or more data structures storing associations between types of medical reports and patient medical information, and use the associations to retrieve patient information related to the type of medical report.
11. The apparatus of claim 1 , wherein the executable instructions, when executed by the one or more processors, further configure the one or more processors to select multimedia content to include in the medical report based at least in part on a severity of the patient's medical condition.
12. The apparatus of claim 1 , wherein the executable instructions, when executed by the one or more processors, further configure the one or more processors to select a greeting segment for the medical report based at least in part on one or more of the patient's race, ethnicity, culture, education, geographic location, or severity of prognosis.
13. The apparatus of claim 1 , wherein the executable instructions, when executed by the one or more processors, further configure the one or more processors to select an explanation segment based at least in part on one or more of the patient's race, age, gender, ethnicity, culture, language, education, geographic location, or severity of prognosis.
14. The apparatus of claim 1 , wherein the executable instructions, when executed by the one or more processors, further configure the one or more processors to select a results segment based at least in part on one or more of the patient's race, age, gender, ethnicity, culture, language, education, geographic location, or severity of prognosis.
15. The apparatus of claim 1 , wherein the executable instructions, when executed by the one or more processors, further configure the one or more processors to select a conclusion segment based on one or more of the patient's race, age, gender, ethnicity, culture, language, education, geographic location, or severity of prognosis.
16. The apparatus of claim 1 , wherein the executable instructions, when executed by the one or more processors, further configure the one or more processors to access one or more data structures configured to store associations related to normality, risk, treatment type, and treatment benefit of medical conditions, and to use the associations to automatically determine normality, risk, treatment type, and treatment benefit information to include in the report based on the patients test results.
17. The apparatus of claim 1 , wherein the executable instructions, when executed by the one or more processors, further configure the one or more processors to generate an updated medical report based on a previously generated medical report, and new patient medical information.
18. A non-transitory computer readable medium for generating a multi-media medical report for a patient, the medical report associated with one or more tests of the patient, the computer readable medium having program instructions for causing one or more hardware processors to perform a method of:
receiving a medical report generation request, the medical report generation request indicating particular patient and a type of medical report;
retrieving, from a computer medium in communication with the one or more hardware processors, patient information associated with the patient indicated in the medical report generation request, the patient information comprising characteristics associated with the patient including age, gender, and language of the patient;
retrieving, from a computer medium in communication with the one or more hardware processors and based on the type of medical report, patient medical information associated with the patient indicated in the medical report generation request, wherein the patient medical information includes
test results of one or more test performed on the patient,
and one or more medical images depicting target features of the patient's body, the one or more images including one or more computed tomography (CT) images from a set of CT images,
measurements of lumen, vessel walls, plaque of coronary vessels, and visualizations of vessels of the patient including a straightened multiplanar reformat (SMPR) vessel view depicting areas of good and/or bad plaque, determined automatically based at least in part by applying a machine learning algorithm to the one or more CT images, and;
retrieving, from a computer medium in communication with the one or more hardware processors, report content associated with the patient information and the type of medical report, the report content comprising
multimedia content that is associated with the patient information but not related to a specific patient, the multimedia content including
a greeting segment in the language of the patient,
an explanation segment in the language of the patient explaining a type of test conducted,
a results segment in the language of the patient presenting the test results and analysis performed on the patient, the test results and analysis including the one or more of the measurements of the lumen, vessel walls, and/or plaque of coronary arteries, and further including the visualizations of vessels of the patient including the straightened multiplanar reformat (SMPR) vessel view depicting areas of good and/or bad plaque,
an explanation segment in the language of the patient explaining the test results, and
a conclusion segment in the language of the patient;
generating, using the retrieved patient information, patient medical information, and report content, a medical report configured to presented on a computer display, the medical report including, in the language of the patient, a greeting, an explanation of the type of test conducted, the test results and analysis preformed on the patient, and a conclusion; and
displaying the medical report on a computer display.
19. The computer readable medium of claim 18 , wherein the one or more of the CT images are generated non-invasively using a normalization device, wherein the normalization device improves accuracy of the non-invasive medical image analysis.
20. A method for generating a multi-media medical report for a patient, the medical report associated with one or more tests of the patient and having one or more medical images including one or more computed tomography (CT) images, the patient's medical information comprises measurements of lumen, vessel walls and plaque of coronary vessels determined from a set of computed tomography (CT) images by image processing, and the one or more CT images rendered from the set of CT images, the method comprising:
receiving a medical report generation request, the medical report generation request indicating particular patient and a type of medical report;
retrieving, from a computer medium in communication with the one or more hardware processors, patient information associated with the patient indicated in the medical report generation request, wherein the patient information comprising characteristics associated with the patient including age, gender, and language of the patient;
retrieving, from a computer medium in communication with the one or more hardware processors and based on the type of medical report, patient medical information associated with the patient indicated in the medical report generation request, wherein the patient medical information includes
test results of one or more test performed on the patient, and
one or more medical images depicting target features of the patient's body, the one or more images including one or more computed tomography (CT) images from a set of CT images;
measurements of lumen, vessel walls, plaque of coronary vessels, and visualizations of vessels of the patient including a straightened multiplanar reformat SMPR) vessel view depicting areas of good and/or bad plaque, determined automatically based at least in part by applying a machine learning algorithm to the one or more CT images, and;
retrieving, from a computer medium in communication with the one or more hardware processors, report content associated with the patient information and the type of medical report, the report content comprising
multimedia content that is associated with the patient information but not related to a specific patient, the multimedia content including
a greeting segment in the language of the patient,
an explanation segment in the language of the patient explaining a type of test conducted,
a results segment in the language of the patient for presenting the test results and analysis performed on the patient, the test results and analysis including the one or more of the measurements of the lumen, vessel walls, and/or plaque of coronary arteries, and further including the visualizations of vessels of the patient including the straightened multiplanar reformat (SMPR) vessel view depicting areas of good and/or bad plaque,
an explanation segment in the language of the patient explaining the test results, and a conclusion segment in the language of the patient;
generating, using the retrieved patient information, patient medical information, and report content, a medical report configured to presented on a computer display, the medical report including, in the language of the patient, a greeting, an explanation of the type of test conducted, the test results and analysis preformed on the patient, and a conclusion; and
displaying the medical report on a computer display,
wherein the method is performed by one or more hardware processors executing instruction on a non-transitory computer readable medium.