Identifying aorta exit points from imaging data

• US 8,103,074 B2
• Filed: 06/22/2011
• Issued: 01/24/2012
• Est. Priority Date: 10/25/2006
• Status: Expired due to Fees

• Current Assignee: Rcadia Medical Imaging, Ltd.
• Original Assignee: Rcadia Medical Imaging, Ltd.
• Inventors: Begelman, Grigory, Goldenberg, Roman, Levanon, Shai, Ohayon, Shay, Walach, Eugene
• Primary Examiner(s): Perungavoor, Sath V
• Assistant Examiner(s): HEIDEMANN, JASON E
• Application Number:
  US13/165,906
• Publication Number:
  US 20110249877A1
• Time in Patent Office: 216 Days
• Field of Search: None
• US Class Current: 382/128
• CPC Class Codes: G06T 2207/30048 Heart; Cardiac
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 2201/031 of internal organs

Abstract

A method of defining a heart region from imaging data is provided. Received imaging data is projected into a first plane. A first threshold is applied to the first plane of data to eliminate data associated with air. A largest first connected component is identified from the first threshold applied data. A first center of mass of the identified largest first connected component is calculated to define a first coordinate and a second coordinate of the heart region. The received imaging data is projected into a second plane, wherein the second plane is perpendicular to the first plane. A second threshold is applied to the second plane of data to eliminate data associated with air. A largest second connected component is identified from the second threshold applied data. A second center of mass of the identified largest second connected component is calculated to define a third coordinate of the heart region.

Claims

1. A method of identifying aorta exit points from imaging data, the method comprising:

identifying an aorta object from imaging data;

calculating a vesselness score for a plurality of voxels in a ring around the identified aorta object;

applying a first threshold to the calculated vesselness score for the plurality of voxels;

identifying a possible exit point based on the applied first threshold;

if greater than one possible exit point is identified, identifying a closest possible exit point to the aorta object; and

if greater than one closest possible exit point is identified, identifying an exit point by selecting the closest possible exit point having a maximum width.

2. The method of claim 1, wherein identifying the aorta object comprises:

(a) selecting a slice of data from the imaging data;

(b) applying a second threshold to the selected slice of data to define voxels above the second threshold;

(c) identifying a connected component from the defined voxels;

(d) eliminating the identified connected component from consideration as the aorta object if a size value of the identified connected component is below a size threshold;

(e) if the identified connected component is not eliminated, comparing the identified connected component with an aorta candidate object identified in a previous slice of data;

(f) assigning the identified connected component to the aorta candidate object based on a matching comparison;

(g) creating a new aorta candidate object based on a non-matching comparison; and

(h) repeating (a)-(g) for a plurality of slices to identify aorta candidate objects; and

(i) selecting the aorta object from the identified aorta candidate objects.

3. The method of claim 2, wherein comparing the identified connected component with the aorta candidate object comprises:

calculating a center of the identified connected component;

comparing the calculated center with a center of the aorta candidate object calculated from a previous slice; and

if the calculated center of the identified connected component is within a number of pixels of the center of the aorta candidate object, the identified connected component is determined to match the aorta candidate object.

4. The method of claim 3, further comprising:

if the calculated center of the identified connected component is not within the number of pixels of the center of the aorta candidate object, the identified connected component is determined not to match the aorta candidate object.

5. The method of claim 3, wherein the number of pixels is twenty.

6. The method of claim 2, wherein the first threshold is approximately 200 Hounsfeld units.

7. The method of claim 2, further comprising eliminating the identified connected component from consideration as the aorta object if a compactness value of the identified connected component indicates the identified connected component is too compact to be an aorta object.

8. The method of claim 2, further comprising applying a morphological filter to the defined voxels.

9. The method of claim 2, wherein the selected aorta object is closest to an upper, left corner of the imaging data.

10. The method of claim 2, further comprising, after (h), eliminating a candidate from the identified aorta candidate objects that has a length less than a number of slices.

11. The method of claim 10, wherein the number of slices is twenty.

12. The method of claim 1, further comprising filtering an identified possible exit point from consideration as the exit point based on a size value of the identified possible exit point.

13. The method of claim 1, further comprising filtering an identified possible exit point from consideration as the exit point based on an incident angle of the identified possible exit point relative to the aorta object.

14. The method of claim 1, further comprising filtering an identified possible exit point from consideration as the exit point based on a location of the identified possible exit point relative to the aorta object.