System and method for tree-model visualization for pulmonary embolism detection

• US 7,599,535 B2
• Filed: 08/01/2005
• Issued: 10/06/2009
• Est. Priority Date: 08/02/2004
• Status: Active Grant

• Current Assignee: Siemens Healthineers AG (Siemens AG)
• Original Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Inventors: Novak, Carol L., Kiraly, Atilla Peter
• Primary Examiner(s): Bali; Vikkram
• Assistant Examiner(s): Bayat; Ali
• Application Number:
  US11/194,252
• Publication Number:
  US 20060023925A1
• Time in Patent Office: 1,527 Days
• Field of Search: 382/100, 382/128, 382/130, 382/131, 382/132, 382/133, 382/165, 382/240, 600/407, 600/410, 250/363.02, 250/363.01
• US Class Current: 382/128
• CPC Class Codes: G06T 19/00 Manipulating 3D models or images for computer graphics
• 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 2207/20044 Skeletonization; Medial axis transform
• CPC Class Codes: G06T 2207/30061 Lung
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 2219/021 Flattening
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/155 involving morphological operators
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes

Abstract

A system and method for tree-model visualization for detecting an abnormality in an anatomical tree structure are provided. The method comprises: fitting a tree-model to an anatomical tree structure; converting branches of the tree-model into first two-dimensional branch images; and arranging the first two-dimensional branch images in a hierarchical order to form a second two-dimensional image.

Claims

1. A method for tree-model visualization for detecting an abnormality in an anatomical tree structure, comprising:

fitting a tree-model to a three-dimensional (3D) image of a segmented anatomical tree structure, said fitting further comprising the steps of;

defining a root site for the anatomical tree structure;

computing a skeleton of the segmented anatomical tree structure;

forming a raw tree-structure using the skeleton;

eliminating false branches in the raw tree-structure;

smoothing and centering the skeleton; and

assigning direction vectors to points in the segmented anatomical tree structure;

converting each branch of the tree-model into a two-dimensional (2D) branch image; and

forming a 2D image that presents the 2D branch images.

2. The method of claim 1, wherein the anatomical tree structure is segmented by using one of a thresholding and size-based labeling, line-filter based or structure tensor-based segmentation technique.

3. The method of claim 1, wherein the tree-model is fit by using one of a vessel-based tracking technique, skeletonization, distance transform or level-set based tree-model computation technique.

4. The method of claim 1, wherein the branches of the tree-model are converted into the 2D branch images by using one of an unrolling, side-by-side display, rotating structure or 2D maximum intensity projection technique.

5. The method of claim 1, wherein the anatomical tree structure is one of a vessel tree or airway tree.

6. The method of claim 1, wherein the anatomical tree structure is acquired using one of a computed tomography or magnetic resonance imaging technique.

7. The method of claim 1, wherein the abnormality is one of a pulmonary embolism, airway stenosis or brain aneurysm.

8. A computer readable medium tangibly embodying a program of instructions executable by a processor to perform method steps for tree-model visualization to detect an abnormality in an anatomical tree structure, the method steps comprising:

fitting a tree-model to a three-dimensional (3D) image of a segmented anatomical tree structure, said fitting further comprising the steps of;

defining a root site for the anatomical tree structure;

computing a skeleton of the segmented anatomical tree structure;

forming a raw tree-structure using the skeleton;

eliminating false branches in the raw tree-structure;

smoothing and centering the skeleton; and

assigning direction vectors to points in the segmented anatomical tree structure;

converting each branch of the tree-model into a two-dimensional (2D) branch image; and

forming a 2D image that presents the 2D branch images.

9. The method of claim 8, further comprising:

displaying the 2D image that presents the 2D branch images in a hierarchical order.

10. The method of claim 9, further comprising:

observing branches in the 2D image that presents the 2D branch images in a hierarchical order.

11. The method of claim 10, further comprising:

receiving a branch selection; and

obtaining an original axial view of image data of the branch or 3D rendering of the branch.

12. The method of claim 11, wherein when the selected branch includes an abnormality, the abnormality is one of a pulmonary embolism, airway stenosis or brain aneurysm.

13. A system for tree-model visualization for detecting an abnormality in an anatomical tree structure, comprising:

a memory device for storing a program;

a processor in communication with the memory device, the processor operative with the program to;

fit a tree-model to a three-dimensional (3D) image of a segmented anatomical tree structure, the fitting further comprising the steps of;

define a root site for the anatomical tree structure;

compute a skeleton of the segmented anatomical tree structure;

form a raw tree-structure using the skeleton;

eliminate false branches in the raw tree-structure;

smooth and center the skeleton; and

assign direction vectors to points in the segmented anatomical tree structure;

convert each branch of the tree-model into a two-dimensional (2D) branch image; and

form a 2D image that presents the 2D branch images.

14. The system of claim 13, wherein the anatomical tree structure is segmented by using one of a thresholding and size-based labeling, line-filter based or structure tensor-based segmentation technique.

15. The system of claim 13, wherein the tree-model is fit by using one of a vessel-based tracking technique, skeletonization, distance transform or level-set based tree-model computation technique.

16. The system of claim 13, wherein the branches of the tree-model are converted into the 2D branch images by using one of an unrolling, side-by-side display, rotating structure or 2D maximum intensity projection technique.

17. The system of claim 13, wherein the anatomical tree structure is one of a vessel tree or airway tree.

18. The system of claim 13, wherein the anatomical tree structure is acquired using one of a computed tomography or magnetic resonance imaging device.

19. The system of claim 13, wherein the abnormality is one of a pulmonary embolism, airway stenosis or brain aneurysm.