IMAGE DISPLAY OF A CENTERLINE OF TUBULAR STRUCTURE

• US 20140363065A1
• Filed: 05/09/2014
• Published: 12/11/2014
• Est. Priority Date: 09/09/2011
• Status: Active Grant

• Current Assignee: Calgary Scientific Inc.
• Original Assignee: Calgary Scientific Inc.
• Inventors: Taerum, Torin Arni, Draper, Jonathan Neil, Newton, Robert George
• Granted Patent: US 9,443,303 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 5/02014 Determining aneurysm
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 6/466 adapted to display 3D data
• CPC Class Codes: A61B 6/481 involving the use of contrast agents
• CPC Class Codes: A61B 6/5205 involving processing of raw data to produce diagnostic data
• CPC Class Codes: A61B 8/466 adapted to display 3D data 3D imaging and stereoscopic displays in devices for short-range imaging with acoustic waves G01S15/8993 and G01S7/52068, respectively; 3D image rendering G06T15/00; manipulating 3D models for computer graphics G06T19/00
• CPC Class Codes: A61B 8/481 involving the use of contrast agent, e.g. microbubbles introduced into the bloodstream analysis of echo signal exploiting properties of a contrast enhancer in devices for short-range imaging with acoustic waves G01S7/52039
• CPC Class Codes: A61B 8/483 involving the acquisition of a 3D volume of data
• CPC Class Codes: A61B 8/5207 involving processing of raw data to produce diagnostic data, e.g. for generating an image reconstruction G06T11/00
• CPC Class Codes: G06F 2203/04806 Zoom, i.e. interaction techniques or interactors for controlling the zooming operation
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06F 3/0488 using a touch-screen or digitiser, e.g. input of commands through traced gestures
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs
• CPC Class Codes: G06T 19/00 Manipulating 3D models or images for computer graphics
• CPC Class Codes: G06T 19/003 Navigation within 3D models or images
• CPC Class Codes: G06T 2200/24 involving graphical user interfaces [GUIs]
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/10136 3D ultrasound image
• CPC Class Codes: G06T 2207/20076 : Probabilistic image processing
• CPC Class Codes: G06T 2207/30101 : Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 2210/41 : Medical
• CPC Class Codes: G06T 2219/028 : Multiple view windows (top-side-front-sagittal-orthogonal)
• CPC Class Codes: G06T 7/0012 : Biomedical image inspection
• CPC Class Codes: G06T 7/12 : Edge-based segmentation
• 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
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders

Abstract

Systems and methods for determining a centerline of a tubular structure from volumetric data of vessels where a contrast agent was injected into the blood stream to enhance the imagery for centerlining. Given a 3D array of scalar values and a first and second point, the system and methods iteratively find a path from the start position to the end position that lies in the center of a tubular structure. A user interface may be provided to visually present and manipulate a centerline of the tubular structure and the tubular structure itself.

Claims

1. A method for determining a centerline of a tubular structure using a processor of a computing device, comprising:

receiving, at a computing device, volumetric data representative of the tubular structure and a selection of a first point and a second point along a length of the tubular structure;

initializing a minimal range of data values associated with a cross section of the tubular structure;

iteratively generating positions associated with two discrete curves from each point toward the other point, the positions initially moving along a direction vector defined at each point, the iteratively generating comprising;

defining a cross section in a plane of the tubular structure;

choosing a next point on each of the two discrete curves in accordance with a smallest area among plural cross sections determined at each next point on each of the two discrete curves;

for each of the two discrete curves, moving in a direction normal to the cross section having the smallest area;

determining if the discrete curves have terminated;

if the discrete curves have terminated, then determining if a length of a result of a curve in a present iteration is shorter than a length of a curve as determined in a previous iteration; and

caching the result of the curve in the present iteration pass if it is determined that the length of the result of the curve in the present iteration is shorter, otherwise maintaining the length of the curve as determined in the previous iteration;

increasing the range of data values for a next iteration; and

terminating the iterative process when a length of a joined curve is longer than a joined curve of the previous iteration, the joined curve of the previous iteration corresponding to the centerline, otherwise returning to iteratively generating positions.

2. The method of claim 1, wherein initializing the data range comprises determining an area of the tubular structure at the starting point and ending point associated with range of data values.

3. The method of claim 1, wherein the two discrete curves are Non-Uniform Rational B-Spline (NURBS) curves.

4. The method of any of claim 1, determining the direction for each of the discrete curves comprising defining a plane at a point that describes a cross section of the tubular structure, wherein the cross section has a smallest area as compared to a second plane perturbed in a different direction several directions about the point.

5. The method of claim 1, moving in a direction normal to the cross section having the smallest area, further comprising:

performing a local search to determine a pixel having a highest intensity; and

moving to the pixel having the highest intensity.

6. The method of any of claim 1, further comprising generating a contour of the tubular structure.

7. The method of any of claim 6, further comprising detecting a branch in the tubular structure using at least one of detecting curvature of the tubular structure, detecting a change in circularity of the tubular structure, and measuring a change in area inside the contour.

8. The method of claim 6, further comprising adjusting the contour by replacing the range of data values the cross sections associated with the branch with an approximation of the range of data values in a non-branching tubular structure.

10. The method of claim 1, wherein the volumetric data is a multi-dimensional medical image.

11. The method of claim 1, wherein the tubular structure is a vessel.

12. The method of claim 11, wherein the vessel is located near bone or the base of the skull.

9. The method of claim 9, further comprising:

determining an aneurysm in the tubular structure by determining ends of the aneurysm by considering an area of the contour area as a function of position along a length of the centerline of the tubular structure; and

locating marker points along the length with a large second derivative magnitude,

wherein the marker points correspond to a neck at each end of the aneurysm.

13. A method for determining a centerline of a tubular structure using a processor of a computing device, comprising:

receiving, at a computing device, volumetric data representative of the tubular structure and a selection of a first point and a second point along a length of the tubular structure;

initializing a minimal range of data values associated with a cross section of the tubular structure; and

iteratively generating positions associated with two discrete curves from each point toward the other point, the positions initially moving along a direction vector defined at each point toward each other point until it is determined if the two discrete curves have terminated or if the two discrete curves have joined,

if the two discrete curves have terminated, further determining if an incomplete result is better than a previous incomplete result and updating a cache if the incomplete result is better; and

if the two discrete curves have joined, further determining if a complete result is better than a previous complete result and updating the cache if the complete result is better.

14. The method of claim 13, further comprising:

at a current point on each of the two discrete curves, defining a plane in the tubular structure perpendicular to a current direction vector and passing through the current point, the plane defining a cross section of the tubular structure;

choosing a next point on each of the two discrete curves, the next point being associated with the cross section having a smallest area among plural cross sections determined at the next point on each of the two discrete curves; and

for each of the two discrete curves, moving in a direction normal to the cross section having the smallest area.

15. The method of claim 14, choosing a next point on each of the two discrete curves, further comprising:

performing a local search to determine a pixel having a highest intensity; and

moving to the pixel having the highest intensity.

16. The method of claim 13, further comprising increasing the range of data values for a next iteration.

17. The method of claim 16, further comprising:

determining if the range has grown to greater than a predetermined number of times larger than an initial range;

determining if the centerline has been determined; and

if so, providing the centerline as a results; and

if not, providing the incomplete result from the cache.

18. The method of claim 13, wherein if the two discrete curves have not terminated and the two discrete curves have not joined, the method further comprising:

determining if the incomplete result is better than a previous incomplete result during a same iteration and updating a cache if the incomplete result is better that the previous incomplete result during the same iteration.

19. The method of claim 13, wherein if the two discrete curves have terminated, the determining is performed in accordance with the following relationship:

if (gap>

=distance)

quality=0

otherwise

quality=(distance−

gap)×

(distance−

gap)/(distance×

length),

wherein the distance equals a distance between two starting points, the length equals a total length of the two discrete curves, a gap equals a remaining distance between final end points of the two discrete curves, and the quality ranges from 0 to 1, with 1 being a best theoretical achievable quality.

20. The method of claim 13, wherein the tubular structure is a vessel.