SYSTEM AND METHOD FOR CONTROLLING USER REPEATABILITY AND REPRODUCIBILITY OF AUTOMATED IMAGE ANNOTATION CORRECTION

• US 20200134897A1
• Filed: 12/23/2019
• Published: 04/30/2020
• Est. Priority Date: 09/25/2013
• Status: Active Grant

• Current Assignee: Heartflow Inc.
• Original Assignee: Heartflow Inc.
• Inventors: GRADY, Leo, SCHAAP, Michiel
• Granted Patent: US 11,742,070 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/5866 using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04845 for image manipulation, e.g. dragging, rotation, expansion or change of colour
• CPC Class Codes: G06T 11/60 Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/97 Determining parameters from multiple pictures depth or shape recovery from multiple images G06T7/55; stereo camera calibration G06T7/85
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing

Abstract

Systems and methods are disclosed for controlling image annotation. One method includes acquiring a digital representation of image data and generating a set of image annotations for the digital representation of the image data. The method also may include determining an association between members of the set of image annotations and generating one or more groups of members based on the association. A representative annotation from the one or more groups may also be determined, presented for selection, and the selection may be recorded in memory.

Claims

1-20. -20. (canceled)

21. A computer-implemented method of controlling image annotation, using at least one computer system, the method comprising using a processor for:

generating, by the at least one computer system, a plurality of image segmentations of anatomic features identified within a digital representation of image data;

generating one or more groups of image segmentations, a given group of the one or more groups comprising one or more image segmentations among the generated plurality of image segmentations;

determining, by the at least one computer system, a representative segmentation for the given group of the one or more groups, the representative segmentation being determined as a segmentation among the one or more image segmentations of the given group closest to an average segmentation of the one or more image segmentations of the given group; and

presenting, by the at least one computer system, the representative segmentation of the given group of the one or more groups for selection or correction by a user.

22. The computer-implemented method of claim 21, further comprising the following steps prior to the step of generating the plurality of image segmentations of features identified within the image data:

adjusting the digital representation of image data; and

generating, by the at least one computer system, alternative image segmentations of anatomic features identified within the adjusted digital representation of image data.

23. The computer-implemented method of claim 21, further comprising:

determining, by the at least one computer system, one or more associations between members of a set of image segmentations of the plurality of image segmentations,

wherein the given group comprising the one or more image segmentations is generated based on the determined one or more associations.

24. The computer-implemented method of claim 21, wherein the digital representation of image data is acquired electronically via a network.

25. The computer-implemented method of claim 21, wherein the representative segmentation identifies anatomic features identified within the image data.

26. The computer-implemented method of claim 21, wherein the plurality of image segmentations are generated using multiple image analysis algorithms.

27. The computer-implemented method of claim 23, wherein each of the one or more associations between members of the set of image segmentations is determined by computing a dice coefficient.

28. The computer-implemented method of claim 21, wherein generating the one or more groups of image segmentations includes generating the one or more groups of image segmentations via a cluster algorithm.

29. The computer-implemented method of claim 21, wherein the cluster algorithm includes spectral partitioning and isoperimetric portioning.

30. The computer-implemented method of claim 21, wherein the image data is a portion of a body organ.

31. A system of controlling image annotation, the system comprising:

a data storage device storing instructions for controlling image segmentation; and

a processor configured to execute the instruction to perform a method including;

generating a plurality of image segmentations of anatomic features identified within a digital representation of image data;

generating one or more groups of image segmentations, a given group of the one or more groups comprising one or more image segmentations among the generated plurality of image segmentations;

determining a representative segmentation for the given group of the one or more groups, the representative segmentation being determined as a segmentation among the one or more image segmentations of the given group closest to an average segmentation of the one or more image segmentations of the given group; and

presenting the representative segmentation of the given group of the one or more groups for selection or correction by a user.

32. The system of claim 31, wherein the processor is further configured to adjust the digital representation of image data;

and generate, by the at least one computer system, alternative image segmentations of anatomic features identified within the adjusted digital representation of image data.

33. The system of claim 31, wherein the processor is further configured to electronically acquire the digital representation of image data via a network.

34. The system of claim 31, wherein the processor is further configured to determine one or more associations between members of a set of image segmentations of the plurality of image segmentations,

wherein the given group comprising the one or more image segmentations is generated based on the determined one or more associations.

35. The system of claim 31, wherein the processor is further configured to automatically generate the plurality of image segmentations using multiple image analysis algorithms.

36. The system of claim 34, wherein the processor is configured to determine each of the one or more associations between members of the set of image segmentations by computing a dice coefficient.

37. The system of claim 34, wherein processor is configured to generate the one or more groups of image segmentations via a cluster algorithm.

38. The system of claim 37, wherein the cluster algorithm includes spectral partitioning and isoperimetric portioning.

39. A non-transitory computer-readable medium for use on a computer system containing computer-executable programming instructions for controlling image annotation, the instructions being executable by the computer system for:

generating a plurality of image segmentations of anatomic features identified within a digital representation of image data;

generating one or more groups of image segmentations, a given group of the one or more groups comprising one or more image segmentations among the generated plurality of image segmentations;

determining a representative segmentation for the given group of the one or more groups, the representative segmentation being determined as a segmentation among the one or more image segmentations of the given group closest to an average segmentation of the one or more image segmentations of the given group; and

presenting the representative segmentation of the given group of the one or more groups for selection or correction by a user.

40. The non-transitory computer readable medium of claim 39, the instructions being executable by the computer system further comprising determining one or more associations between members of a set of image segmentations of the plurality of image segmentations,

wherein the given group comprising the one or more image segmentations is generated based on the determined one or more associations.