System for modeling static and dynamic three dimensional anatomical structures by 3-D models

• US 6,816,607 B2
• Filed: 05/16/2001
• Issued: 11/09/2004
• Est. Priority Date: 05/16/2001
• Status: Expired due to Fees

• Current Assignee: Siemens Healthcare GMBH (Siemens AG)
• Original Assignee: Siemens Corporate Research Incorporated (Siemens AG)
• Inventors: Gupta, Alok, Jolly, Marie-Pierre, OʼDonnell, Thomas
• Primary Examiner(s): WERNER, BRIAN P
• Application Number:
  US09/858,368
• Publication Number:
  US 20020172407A1
• Time in Patent Office: 1,273 Days
• Field of Search: 382/128, 382/131, 382/154, 382/285, 345/420
• US Class Current: 382/131
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/20116 Active contour; Active surface; Snakes
• CPC Class Codes: G06T 2207/30048 Heart; Cardiac
• CPC Class Codes: G06T 2210/41 Medical
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/149 involving deformable models, e.g. active contour models

Abstract

The present invention relates to a system of modeling a three dimensional target object which is represented by a plurality of cross-sectional images in order to provide a representative corresponding three dimensional model. The invention selects an initial model from a plurality of available initial models. This selection involves identifying an initial model based on physical similarity to the target object and then superimposing an initial model upon the target object, for each of the plurality of cross-sectional images. A determination is then made of an intersection contour of the initial model and a cross-sectional image of the target object and the determined intersection contour is refined in order to more closely delineate the target object. By sub-sampling points which represent the refined determined intersection contour, the invention obtains a sub-sampled contour dataset. The initial model is then adjusted towards the sub-samples contour to obtain a representative three dimensional model of the target object.

Claims

1. In an image processing system, a method of modeling a three dimensional target object, varying in shape between different operational phases and represented by a plurality of cross-sectional images, to provide a representative corresponding dynamic three dimensional model, comprising the steps of:

for a first shape of said target object corresponding to a first position of the target object during its operational phase,

approximately superimposing an initial model upon said target object, the initial model estimating a position of an inner and outer wall of the target object;

for each of said plurality of cross-sectional images,

determining an intersection contour of said initial model and a cross-sectional image of said target object;

refining said determined intersection contour to more closely delineate said target object; and

dynamically adjusting said initial model toward said refined determined intersection contour to provide a representative three dimensional model of said target object in motion; and

for a second shape of said target object, said second shape of said target object representing said target object at a second position during its operational phase,

repeating the previous steps; and

for subsequent shapes of the target object, each subsequent shape representing said target object at a subsequent position during its operational phase,

repeating the previous steps until the target object has reached a desired position in the operational phase.

2. A method according to claim 1 including the step of

selecting said initial model from a plurality of available initial models by identifying an initial model most closely fitting said target object.

3. A method according to claim 2, including the step of

identifying said initial model most closely fitting said target object by positioning and rotating an image representing said initial model to most closely align with an image representing said target object.

4. A method according to claim 1 wherein said step of refining said determined intersection contour includes the step of

applying image processing functions to image data points representing said determined intersection contour to provide points representing a contour more closely delineating said target object.

5. A method according to claim 4 wherein said image processing functions include a 2-D segmentation algorithm.

6. A method according to claim 1 including the step of

employing said representative three dimensional model of (a) said target object first shape and (b) said target object second shape or said target object subsequent shape, in determining at least one of, (i) volume difference between said first and second shapes, (ii) strain on said target object and (iii) a suitable replacement for said target object.

7. A method according to claim 1 wherein

said three dimensional target object varies in shape, between said first shape and said second shape and said subsequent shapes associated with corresponding operational phases, on a substantially periodic basis.

8. A method according to claim 1 wherein said three dimensional target object is a section of a heart.

9. A method according to claim 1 wherein said three dimensional target object is a body organ.

10. A method according to claim 1 wherein said different operational phases comprise at least one of (a) different phases of heart operation, (b) different movement phases of a skeletal structure, (c) different states of an anatomical organ.

11. A method according to claim 1 including the step of

employing a scale factor to weight data locations from said sub-sampled contour dataset in refining said determined intersection contour to more closely delineate said target object.

12. A method according to claim 1 including the step of

selecting an initial model from a plurality of available initial models by identifying an initial model based on physical similarity to said target object.

13. A method according to claim 1 wherein after said step of approximately superimposing an initial model upon said target object, said method of claim 9 is performed automatically for a target object without User entry of data.

14. In an image processing system, a method of modeling a three dimensional target object, varying in shape between different operational phases and represented by a plurality of cross-sectional images, to provide a representative corresponding dynamic three dimensional model, comprising the steps of:

for a first shape of said target object corresponding to a first position of the target object during its operational phase,

approximately superimposing an initial model upon said target object, the initial model estimating a position of an inner and outer wall of the target object;

for each of said plurality of cross-sectional images,

determining an intersection contour of said initial model and a cross-sectional image of said target object;

refining said determined intersection contour to more closely delineate said target object;

sub-sampling points representing said refined determined intersection contour to provide a sub-sampled contour dataset; and

dynamically adjusting said initial model toward said sub-sampled contour to provide a representative three dimensional model of said target object in motion; and

for a second shape of said target object, said second shape of said target object representing said target object at a second position during its operational phase,

repeating the previous steps; and

for subsequent shapes of the target object, each subsequent shape representing said target object at a subsequent position during its operational phase,

repeating the previous steps until the target object has reached a desired position in the operational phase.

15. A method according to claim 14 including the step of

employing said representative three dimensional model of (a) said target object first shape and (b) said target object second shape or said target object subsequent shape, in determining at least one of, (i) volume difference between said first and second shapes, (ii) strain on said target object and (iii) a suitable replacement for said target object.

16. A method according to claim 14 including the step of

selecting an initial model from a plurality of available initial models by identifying an initial model based on physical similarity to said target object.

17. A method according to claim 14 wherein said three dimensional target object is a section of a heart.

18. A method according to claim 14 wherein said three dimensional target object is a body organ.

19. A method according to claim 14 wherein said different operational phases comprise at least one of (a) different phases of heart operation, (b) different movement phases of a skeletal structure, (c) different states of an anatomical organ.

20. A method according to claim 14 including the step of

employing a scale factor to weight data locations from said sub-sampled contour dataset in refining said determined intersection contour to more closely delineate said target object.

21. A method according to claim 14 wherein after said step of approximately superimposing an initial model upon said target object, said method of claim 15 is performed automatically for a target object without User entry of data.