US 6,690,816 B2Granted

Systems and methods for tubular object processing

AssigneeThe University of North Carolina at Chapel Hill

InventorsStephen R. Aylward, Elizabeth Bullitt, Stephen M. Pizer, Daniel Fritsch

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Abstract

Systems and methods are disclosed for processing tubular objects in multi-dimensional images. The processing includes generating representations of tubular objects which enable subsequent analysis. Systems and methods for processing tubular objects in a multi-dimensional image include establishing a seed points in a multi-dimensional image, searching for an extremum point corresponding to a tubular object having a central curve of intensity extrema, and extracting a one-dimensional central track corresponding to the tubular object and extents corresponding to a plurality of cross-sections along the tubular object. A number of embodiments are presented which apply the systems and methods to a variety of imaging applications.

Claims32

Dependent claims

A method for processing at least one tubular object in a multi-dimensional image, comprising:

(a) establishing a seed point in a multi-dimensional image;
(b) searching for an extremum point corresponding to a tubular object having a central curve of intensity extrema;
(c) extracting:
a) a one-dimensional central track corresponding to the tubular object, and b) extents corresponding to a plurality of cross-sections along the tubular object, wherein the plurality of cross-sections intersects the one-dimensional central track;
(d) convolving intensities of image elements within a vicinity of the extremum point with a filter to create the central curve of intensity extrema;
(e) computing a first set of normal vectors at a first position corresponding to the extremum point, the first set of normal vectors being substantially orthogonal to the one-dimensional central track;
(f) computing a first tangent vector at the first position, the first tangent vector being substantially parallel to the one-dimensional central track;
(g) traversing to a second position by stepping from the first position in the direction along the tangent vector using a step size;
(h) computing a second set of normal vectors at the second position, the second set of normal vectors being substantially orthogonal to the one-dimensional central track;
(i) computing a second tangent vector at the second position, the second tangent vector being substantially parallel to the one-dimensional central track;
(j) determining a proximity of the first position and the second position;
(k) searching for an intensity maximum in a space defined by the first set of normal vectors when the second position is not substantially coincident with the central curve of intensity extrema;
and
(l) determining whether at least one stop traversing criteria is met.

11 more elements

A system for processing at least one tubular object in a multi-dimensional image, comprising:

(a) a computer processor;
and
(b) a memory functionally coupled to the computer processor, wherein the memory stores a multi-dimensional image and instructions to be executed by the computer processor, for:
(i) establishing a seed point in the multi-dimensional image;
(ii) searching for an extremum point corresponding to a tubular object having a central curve of intensity extrema
(iii) extracting:
a) a one-dimensional central track corresponding to the tubular object, and b) extents corresponding to a plurality of cross-sections along the tubular object, wherein the plurality of cross-sections intersects the one-dimensional central track;
(iv) convolving intensities of image elements within a vicinity of the extremum point with a filter to create the central curve of intensity extrema;
(v) computing a first set of normal vectors at a first position corresponding to the extremum point, the first set of normal vectors being substantially orthogonal to the one-dimensional central track;
(vi) computing a first tangent vector at the first position, the first tangent vector being substantially parallel to the one-dimensional central track;
(vii) traversing to a second position by stepping from the first position in the direction along the tangent vector using a step size;
(viii) computing a second set of normal vectors at the second position, the second set of normal vectors being substantially orthogonal to the one-dimensional central track;
(ix) computing a second tangent vector at the second position, the second tangent vector being substantially parallel to the one-dimensional central track;
(x) determining a proximity of the first position and the second position;
(xi) searching for an intensity maximum in a space defined by the first set of normal vectors when the second position is not substantially coincident with the central curve of intensity extrema;
and
(xii) determining whether at least one stop traversing criteria is met.

14 more elements

Dependencies are inferred from the claim text.

Facts

Application: 09/828,200Filed 9 Apr 2001 · us provisional application
Priority: 7 Apr 2000
Published: US 2003/0053697 A120 Mar 2003
Granted: 10 Feb 2004
Term ends: Not estimatedThe source records don’t support an estimate.

Classification9 codes

G06T 7/0012
Inspection of images, e.g. flaw detection: biomedical image inspection
G06T 7/11
Segmentation; Edge detection: region-based segmentation
G06T 7/64
Analysis of geometric attributes: of convexity or concavity
G06T 2207/10072
Image acquisition modality: tomographic images