Automatic delineation of heart borders and surfaces from images

• US 20030038802A1
• Filed: 08/23/2002
• Published: 02/27/2003
• Est. Priority Date: 08/23/2001
• Status: Abandoned Application

• Current Assignee: University of Washington
• Original Assignee: University of Washington
• Inventors: Johnson, Richard K., Sheehan, Florence H., McDonald, John Alan
• Application Number:
  US10/227,252
• Publication Number:
  US 20030038802A1
• Time in Patent Office: Days
• US Class Current: 345/420
• CPC Class Codes: G06T 17/30 Polynomial surface description

Abstract

A method for fitting a surface to some portion of a patient'"'"'s heart. In the method, ultrasound imaging is carried out over at least one cardiac cycle, providing a plurality of images in different image planes made with a transducer at known positions and orientations. An operator selects points on some of the images that correspond to the surface of interest, and a surface is automatically fit to the points in three dimensions, using prior knowledge about heart anatomy to constrain the fitted shape to a reasonable result. The operator reviews the fitted surface, in 3D or alternatively, as intersected with the images. If the fit is acceptable, the process is done. Otherwise, the image processing is repetitively carried out, guided by the fitted surface, to produce additional data points, until an acceptable fit is obtained. The resulting output surface can be used in determining cardiac parameters.

Claims

1. A method for determining a surface of a patient'"'"'s organ from sparse data points derived from images along image planes through the patient'"'"'s organ, using a knowledge base of images and surfaces of other such organs, comprising the steps of:

(a) tracing the images of the patient'"'"'s organ to obtain the sparse data points;

(b) deriving a candidate surface by fitting to the sparse data points, using surfaces from the knowledge base, said candidate surface corresponding to an anatomically feasible surface;

(c) intersecting the candidate surface with the image planes corresponding to the images of the patient'"'"'s organ, yielding candidate borders for the patient'"'"'s organ, each candidate border being associated with a different one of the image planes;

(d) determining if the candidate borders are consistent with the images of the patient'"'"'s organ, and if so, employing the candidate surface for the surface of the patient'"'"'s organ, but if not so, adding additional data points determined from the images of the patient'"'"'s organ to the sparse data points and repeating steps (b)-(d) using the sparse data points and additional data points successively added in step (d) until the surface of the patient'"'"'s organ is thus determined.

2. The method of claim 1, wherein the step of adding additional data points comprises the step of manually tracing the images of the patient'"'"'s organ to identify the additional data points.

3. The method of claim 1, wherein the step of adding additional data points comprises the step of automatically detecting the additional data points within the candidate borders.

4. The method of claim 3, wherein the step of automatically detecting the additional data points comprises the steps of:

(a) extracting a plurality of image regions at a plurality of locations along the candidate borders;

(b) using border templates in the knowledge base for the other such organs, wherein each border template corresponds to a different on of the image regions, identifying positions of best fit for each border template in the image region to which it corresponds;

(c) retaining only the positions of best fit that meet predefined criteria; and

(d) computing the additional data points for use in deriving a new candidate surface from the positions of best fit that have been retained.

5. The method of claim 1, wherein the step of deriving a candidate surface comprises the steps of:

(a) determining a fitted surface expressed as a weighted average of shapes included in the knowledge base, said fitted surface being fitted to the sparse data points and any additional data points that have been added;

(b) determining a fit quality for the fitted surface; and

(c) adjusting parameters that define the fitted surface until the fit quality of the fitted surface satisfies a predetermined criteria, thereby yielding the candidate surface equal to a current fitted surface.

6. The method of claim 5, wherein the step of determining the fitted surface comprises the step of adjusting vertex positions of the shapes in the knowledge base until the weighted average conforms to the sparse data points and any additional data points that have been added.

7. The method of claim 1, wherein each intersection of one of the image planes with the candidate surface yields a different candidate border associated with the image plane, said candidate border defining an image region used for determining the additional data points.

8. The method of claim 1, further comprising the steps of displaying the surface of the patient'"'"'s organ and using the surface to compute parameters indicative of a condition of the patient'"'"'s organ.

9. The method of claim 1, further comprising the step of producing the images of the patient'"'"'s organ using an ultrasonic imaging device that is disposed at known positions and orientations relative to the patient'"'"'s organ.

10. The method of claim 1, further comprising the step of displaying the surface that was determined, to enable an operator to determine if the surface is anatomically consistent with the images of the patient'"'"'s organ.

11. The method of claim 1, wherein the patient'"'"'s organ is a heart, and wherein the other such organs are hearts.

12. A method for defining a surface of a patient'"'"'s organ using a knowledge base of border templates derived from imaging other such organs, and sparse data points derived from images along image planes through the patient'"'"'s organ, comprising the steps of:

(a) deriving a candidate surface that fits the sparse data points, said candidate surface corresponding to an anatomically feasible surface;

(b) intersecting the candidate surface with the image planes, yielding candidate borders, each candidate border being associated with a different image plane and the image of the patient'"'"'s organ along the image plane;

(c) for each of a plurality of specific regions along each candidate border, selecting a position at which a corresponding border template most closely matches the image of the patient'"'"'s organ associated with the candidate border, yielding a candidate border point for the region, a current set of candidate border points being thus defined for the candidate borders;

(d) repeating steps (a)-(c) using the sparse data points and successive sets of candidate border points, until the candidate border points comprising a current set of candidate border points do not differ substantially from candidate border point comprising a previous set of candidate border points in an immediately previous iteration, said candidate surface used to select the current set of candidate border points then defining the surface of the patient'"'"'s organ.

13. The method of claim 12, wherein positions that are selected are defined within two dimensions, and wherein the candidate border points are defined within three dimensions, further comprising the step of computing each candidate border point from one of the positions that is selected.

14. The method of claim 13, further comprising the step of computing a similarity measure for each possible location of the border template within one of the specific regions and selecting as the position the location having the highest similarity measure.

15. The method of claim 14, wherein the similarity measure is determined using a cross correlation function.

16. The method of claim 14, further comprising the step of retaining only positions that meet predefined criteria for use in computing the candidate border points.

17. The method of claim 16, wherein the predefined criteria comprises a threshold for the similarity measure, such that positions having a similarity measure below the threshold are not retained.

18. The method of claim 12, wherein each intersection of one of the image planes with the candidate surface yields a different candidate border associated with the image plane, said plurality of specific regions used for determining the candidate border points being disposed at spaced apart intervals around the candidate borders.

19. The method of claim 12, further comprising the steps of displaying the surface of the patient'"'"'s organ and using the surface to compute parameters indicative of a condition of the patient'"'"'s organ.

20. The method of claim 12, further comprising the step of producing the images of the patient'"'"'s organ using an ultrasonic imaging device that is disposed at known positions and orientations relative to the patient'"'"'s organ.

21. The method of claim 12, further comprising the step of displaying the surface that was determined, to enable an operator to determine if the surface is anatomically consistent with the images of the patient'"'"'s organ.

22. The method of claim 12, wherein the patient'"'"'s organ is a heart, and wherein the other such organs are hearts.