Quantitative medical imaging reporting
Advanced reporting systems based on ontology development for quantitative imaging biomarkers, information modeling to integrate heterogeneous data types relevant to quantitative medical analysis, and a knowledge representation framework for their statistical validation.
1. A system comprising a processor and a non-transient storage medium, the storage medium including processor executable instructions implementing a report generation module include a natural language generator, the report generation module configured to:
receive a data set including non-invasive quantitative and objective measurements of one or more biological properties of a patient;
determining anatomical field of views relating to the patient based on the data set, wherein the anatomical field of views include a target, a vessel, and a cross-section level block;
determining one or more pathologies for the patient based on the anatomical field of views and one or more predetermined rules;
process the data set using the natural language generator to automatically provide a natural language narrative including an objectively structured set of a plurality of findings based on the quantitative and objective measurements and wherein the natural language narrative includes the one or more predetermined rules as grammatical elements; and
generate and display a report for the patient, the report including the natural language narrative.
2. The system of claim 1 , wherein the generated report is configured to correlate each of the plurality of findings in the natural language narrative with a specific quantitative data subset supporting that finding.
3. The system of claim 2 , wherein the generated report further includes a user interface configured to enable a user to selectively view the specific quantitative data subset correlated with each of the findings in the natural language narrative.
4. The system of claim 1 , wherein the data set includes a hierarchical data structure including one or more qualitative pathological features which are determined based on the quantitative and objective measurements of the one or more biological properties.
5. The system of claim 4 , wherein the natural language narrative includes an objective natural language interpretation of both the quantitative and objective measurements and the qualitative pathological features.
6. The system of claim 5 , wherein the qualitative pathological features include phenotype classification for a pathology.
7. The system of claim 4 , wherein the hierarchical data structure further includes one or more predictive outcomes for a pathology.
8. The system of claim 7 , wherein the natural language narrative includes an objective natural language interpretation of the one or more predictive outcomes for the pathology.
9. A system comprising a processor and a non-transient storage medium, the storage medium including processor executable instructions implementing a report generation module, the report generation module configured to:
receive a data set including non-invasive quantitative and objective measurements of one or more biological properties of a patient;
determining anatomical field of views relating to the patient based on the data set, wherein the anatomical field of views include a target, a vessel, and a cross-section level block;
determining one or more pathologies for the patient based on the anatomical field of views and one or more predetermined rules; and
use an ontological data model based on the one or more predetermined rules including a taxonomic hierarchy of biomedical concepts related to a domain of biological properties to analyze the data set and generate and display a report for the patient based on ontology from the ontological data model.
10. The system of claim 9 , wherein the report includes longitudinal trend analysis based on ontology from ontological data model.
11. The system of claim 10 , wherein longitudinal trend analysis includes using pre-computed data points and information for a trend from older data sets to reduce processing time.
12. The system of claim 9 , wherein the report utilizes pre-computed data points and information from older data sets to reduce processing time.
13. The system of claim 9 , wherein the ontological data model includes semantic relationships between biomedical concepts.
14. The system of claim 9 , wherein the quantitative and objective measurements include imaging data.
15. The system of claim 9 , wherein the taxonomic hierarchy of biomedical concepts includes a hierarchical characterization of a target anatomical site.
16. The system of claim 15 , wherein the hierarchical characterization of the target anatomical site includes characterization of a vessel, a vessel segment, and a segment cross-section.
17. The system of claim 16 , wherein the hierarchical characterization of the target anatomical site further includes a characterization of an anatomic region for the vessel.
18. The system of claim 9 , wherein the ontological data model includes defines relationships between qualitative pathological features and quantitative and objective measurements of one or more biological properties.
19. The system of claim 18 , wherein the report includes one or more qualitative pathological features for the patient which are automatically and objectively determined based on the ontological data model.
20. The system of claim 19 , wherein the one or more qualitative pathological features include phenotype classification for a pathology.
21. The system of claim 19 , wherein the one or more qualitative pathological features provide for computer aided detection of a pathology.
22. The system of claim 9 , wherein the system includes a client server architecture, wherein the server is configured to receive a request from a client whereby such request triggers the generation of the report.
23. The system of claim 22 , wherein the server is configured to work ahead and pre-compute available report information prior to receiving a client request to reduce processing time.