AUTOMATED SEPARATION OF BINARY OVERLAPPING TREES

• US 20160035088A1
• Filed: 03/14/2014
• Published: 02/04/2016
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Abramoff D. Michael, Department of Veterans Affairs The United States of Government As Represented By
• Original Assignee: The United States of America Represented by The Department of Veterans Affairs, University of Iowa Research Foundation
• Inventors: Abramoff, Michael D., Garvin, Mona K., Qiao, Hu
• Granted Patent: US 10,360,672 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/20044 Skeletonization; Medial axis transform
• CPC Class Codes: G06T 2207/20072 Graph-based image processing
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 2207/30041 Eye; Retina; Ophthalmic
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06T 7/162 involving graph-based methods

Abstract

Provided are systems and methods for analyzing images. An exemplary method can comprise receiving at least one image having one or more annotations indicating a feature. The method can comprise generating training images from the at least one image. Each training image can be based on a respective section of the at least one image. The training images can comprise positive images having the feature and negative images without the feature. The method can comprise generating a feature space based on the positive images and the negative images. The method can further comprise identifying the feature in one or more unclassified images based upon the feature space.

Claims

1. A method for image analysis, comprising:

receiving an image with a plurality of overlapping tree structures;

generating a potential connectivity map (PCM) based on the plurality of tree structures, wherein the PCM comprises segments;

determining potential connectivity between segments and a corresponding cost for each potential connectivity;

processing the PCM to separate the plurality of overlapping tree structures into separate tree structures with a minimal cost; and

outputting the separate tree structures having minimal cost.

2. The method of claim 1, wherein the plurality of overlapping tree structures comprises a plurality of overlapping anatomical vascular trees.

3. The method of claim 2, wherein the segments are vessel segments.

4. The method of claim 3, wherein generating a potential connectivity map (PCM) based on the plurality of tree structures comprises separating vessel centerlines into separated disambiguated longest vessel segments which exhibit no landmarks except at both ends.

5. The method of claim 1, wherein determining potential connectivity between segments and a corresponding cost for each potential connectivity comprises determining neighbor segments from among the segments and determining the potential connectivity between neighbor segments.

6. The method of claim 1, wherein processing the PCM to separate the plurality of overlapping tree structures into separate tree structures with a minimal cost comprises transferring the PCM into a graph model.

7. A system for image analysis, comprising:

a memory having computer-executable instructions encoded thereon; and

at least one processor functionally coupled to the memory and configured, by the computer-executable instructions, for,

receiving an image with a plurality of overlapping tree structures,

generating a potential connectivity map (PCM) based on the plurality of tree structures, wherein the PCM comprises segments,

determining potential connectivity between segments and a corresponding cost for each potential connectivity,

processing the PCM to separate the plurality of overlapping tree structures into separate tree structures with a minimal cost, and

outputting the separate tree structures having minimal cost.

8. The system of claim 7, wherein the plurality of overlapping tree structures comprises a plurality of overlapping anatomical vascular trees.

9. The system of claim 8, wherein the segments are vessel segments.

10. The system of claim 9, wherein generating a potential connectivity map (PCM) based on the plurality of tree structures comprises separating vessel centerlines into separated disambiguated longest vessel segments which exhibit no landmarks except at both ends.

11. The system of claim 7, wherein determining potential connectivity between segments and a corresponding cost for each potential connectivity comprises determining neighbor segments from among the segments and determining the potential connectivity between neighbor segments.

12. The system of claim 7, wherein processing the PCM to separate the plurality of overlapping tree structures into separate tree structures with a minimal cost comprises transferring the PCM into a graph model.

13. A non-transitory computer readable medium having computer-executable instructions encoded thereon for image analysis, said computer-executable instructions adapted to be executed to implement a method comprising:

receiving an image with a plurality of overlapping tree structures;

generating a potential connectivity map (PCM) based on the plurality of tree structures, wherein the PCM comprises segments;

determining potential connectivity between segments and a corresponding cost for each potential connectivity;

processing the PCM to separate the plurality of overlapping tree structures into separate tree structures with a minimal cost; and

outputting the separate tree structures having minimal cost.

14. The non-transitory computer readable medium of claim 13, wherein the plurality of overlapping tree structures comprises a plurality of overlapping anatomical vascular trees.

15. The non-transitory computer readable medium of claim 14, wherein the segments are vessel segments.

16. The non-transitory computer readable medium of claim 15, wherein generating a potential connectivity map (PCM) based on the plurality of tree structures comprises separating vessel centerlines into separated disambiguated longest vessel segments which exhibit no landmarks except at both ends.

17. The non-transitory computer readable medium of claim 13, wherein determining potential connectivity between segments and a corresponding cost for each potential connectivity comprises determining neighbor segments from among the segments and determining the potential connectivity between neighbor segments.

18. The non-transitory computer readable medium of claim 13, wherein processing the PCM to separate the plurality of overlapping tree structures into separate tree structures with a minimal cost comprises transferring the PCM into a graph model.