Automated report generation

1. A computer-implemented method comprising:

receiving selection of an exam for display on one or more displays of a computing system having one or more computer processors, the exam including a plurality of image series, each of the plurality of image series being associated corresponding image series types;

determining an exam characteristic associated with the exam;

accessing a data structure storing an association between the exam characteristic and a report package, the report package comprising a parent report and one or more child reports, the data structure further storing associations between each of the one or more child reports and respective image series types;

selecting from the data structure the report package, wherein the one or more child reports of the report package are configured to receive diagnosis data from a user of the computing system regarding one or more images of respective image series of respective image series types associated with the one or more child reports;

identifying a first image series of the plurality of image series of the exam having a first image series type;

identifying a first child report of the one or more child reports, wherein the first child report is associated with the first image series type;

identifying features of interest in at least one image of the first image series;

determining portions of the first child report corresponding to respective features of interest in the at least one image;

displaying, on the one or more displays, the parent report, the first child report, and the at least one image; and

at least partially superimposing the portions of the first child report on respective corresponding features of interest in the displayed at least one image of the first image series.

2. The computer-implemented method of claim 1 , wherein the portions of the first child report that are at least partially superimposed on the respective corresponding features of interest in the displayed at least one image of the first image series are at least partially transparent.

3. The computer-implemented method of claim 1 further comprising:

automatically analyzing the at least one image of the first image series to automatically identify the one or more features of interest in the at least one image.

4. The computer-implemented method of claim 1 further comprising:

automatically analyzing the first child report to automatically identify important findings in the first child report.

5. The computer-implemented method of claim 4 further comprising:

automatically emphasizing the important findings identified in the first child report.

6. The computer-implemented method of claim 5 , wherein automatically emphasizing comprises at least one or highlighting, capitalizing, bolding, or coloring.

7. The computer-implemented method of claim 1 , wherein the first child report is at least partially graphical so that the user can provide input in an intuitive manner by selecting portions of the first child report associated with graphical anatomical structures.

8. The computer-implemented method of claim 1 further comprising:

in response to receiving diagnosis data from the user of the computing system to the first child report, automatically updating the parent report with similar diagnosis data.

9. The computer-implemented method of claim 1 further comprising:

in response to receiving diagnosis data from the user of the computing system to the at least one image of the first image series, automatically updating the first child report with similar diagnosis data.

10. The computer-implemented method of claim 1 , wherein the exam characteristic comprises at least one of: an exam type, an exam modality, a clinical indication and/or other clinical information, a medical history of a patient, or risk factors associated with the patient.

11. A computing system comprising:

a data structure storing an association between the exam characteristic and a report package, the report package comprising a parent report and one or more child reports, the data structure further storing associations between each of the one or more child reports and respective image series types;

one or more displays; and

one or more computer processors configured with computer-executable instructions in order to:

receive selection of an exam for display on the one or more displays, the exam including a plurality of image series, each of the plurality of image series being associated corresponding image series types;

determine an exam characteristic associated with the exam;

select from the data structure the report package, wherein the one or more child reports of the report package are configured to receive diagnosis data from a user of the computing system regarding one or more images of respective image series of respective image series types associated with the one or more child reports;

identify a first image series of the plurality of image series of the exam having a first image series type;

identify a first child report of the one or more child reports, wherein the first child report is associated with the first image series type;

identify features of interest in at least one image of the first image series;

determine portions of the first child report corresponding to respective features of interest in the at least one image;

display, on the one or more displays, the parent report, the first child report, and the at least one image; and

at least partially superimpose the portions of the first child report on respective corresponding features of interest in the displayed at least one image of the first image series.

12. The computing system of claim 11 , wherein the portions of the first child report that are at least partially superimposed on the respective corresponding features of interest in the displayed at least one image of the first image series are at least partially transparent.

13. The computing system of claim 11 , wherein the one or more computer processors are further configured with computer-executable instructions in order to:

automatically analyze the at least one image of the first image series to automatically identify the one or more features of interest in the at least one image.

14. The computing system of claim 11 , wherein the one or more computer processors are further configured with computer-executable instructions in order to:

automatically analyze the first child report to automatically identify important findings in the first child report.

15. The computing system of claim 14 , wherein the one or more computer processors are further configured with computer-executable instructions in order to:

automatically emphasize the important findings identified in the first child report.

16. The computing system of claim 15 , wherein automatically emphasizing comprises at least one or highlighting, capitalizing, bolding, or coloring.

17. A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by one or more computer processors, cause the one or more computer processors to:

receive selection of an exam for display on one or more displays of a computing system, the exam including a plurality of image series, each of the plurality of image series being associated corresponding image series types;

determine an exam characteristic associated with the exam;

access a data structure storing an association between the exam characteristic and a report package, the report package comprising a parent report and one or more child reports, the data structure further storing associations between each of the one or more child reports and respective image series types;

select from the data structure the report package, wherein the one or more child reports of the report package are configured to receive diagnosis data from a user of the computing system regarding one or more images of respective image series of respective image series types associated with the one or more child reports;

identify a first image series of the plurality of image series of the exam having a first image series type;

identify a first child report of the one or more child reports, wherein the first child report is associated with the first image series type;

identify features of interest in at least one image of the first image series;

determine portions of the first child report corresponding to respective features of interest in the at least one image;

display, on the one or more displays, the parent report, the first child report, and the at least one image; and

at least partially superimpose the portions of the first child report on respective corresponding features of interest in the displayed at least one image of the first image series.

18. The non-transitory computer-readable storage medium of claim 17 , wherein the first child report is at least partially graphical so that the user can provide input in an intuitive manner by selecting portions of the first child report associated with graphical anatomical structures.

19. The non-transitory computer-readable storage medium of claim 17 , wherein, when executed by one or more computer processors, the computer-executable instructions cause the one or more computer processors to further:

in response to receiving diagnosis data from the user of the computing system to the first child report, automatically update the parent report with similar diagnosis data.

20. The non-transitory computer-readable storage medium of claim 17 , wherein, when executed by one or more computer processors, the computer-executable instructions cause the one or more computer processors to further:

in response to receiving diagnosis data from the user of the computing system to the at least one image of the first image series, automatically update the first child report with similar diagnosis data.