ACTIVE CATHETER RECONSTRUCTION FOR INTERVENTIONAL MAGNETIC RESONANCE IMAGING

• US 20130083988A1
• Filed: 09/12/2012
• Published: 04/04/2013
• Est. Priority Date: 09/29/2011
• Status: Active Grant

• Current Assignee: Siemens Healthcare GMBH (Siemens AG)
• Original Assignee: Siemens Corp. (Siemens AG)
• Inventors: Barbot, Julien Christian, Kirchberg, Klaus J.
• Granted Patent: US 9,186,088 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 2090/3983 Reference marker arrangements for use with image guided surgery
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 5/064 using markers A61B5/062 takes precedence

Abstract

A method for device visualization includes receiving a set of physical characteristics including a description of spatial relationships of a plurality of markers within a device. Radiographic data of the device within a subject is acquired. An approximate location of each of the plurality of markers is identified within the radiographic data. A trajectory function is constructed for the device within the subject based on the identified approximate locations of each of the markers and the received set of physical characteristics. A section function is constructed for the device based on the set of physical characteristics and a 3D model is generated for the device based on the constructed trajectory function and the section function. A rendering of the 3D model is displayed on a display device.

Claims

1. A method for device visualization, comprising:

receiving a set of physical characteristics including a description of spatial relationships of a plurality of markers within a device;

acquiring radiographic data of the device within a subject;

identifying an approximate location of each of the plurality of markers within the radiographic data;

constructing a trajectory function for the device within the subject based on the identified approximate locations of each of the markers and the received set of physical characteristics;

constructing a section function for the device based on the set of physical characteristics;

generating a 3D model for the device based on the constructed trajectory function and the section function; and

displaying a rendering of the 3D model on a display device.

4. The method of claim 1, wherein the trajectory function is a mathematical spline function defined by a knot vector, a vector of control points, and a degree of polynomial for the spline function.

5. The method of claim 4, wherein the knot vector and the vector of control points are varied to find a spline function which satisfies one or more constraints of the received set of physical characteristics.

6. The method of claim 5, wherein the spline function is a piecewise-polynomial function of a given degree of polynomial.

7. The method of claim 6, wherein the degree of polynomial for the spline function is three.

8. The method of claim 4, wherein a curve energy of the spline function is minimized.

9. The method of claim 4, wherein the spline function is a B-spline function.

10. The method of claim 4, wherein the spline function is a non-uniform rational B-spline (NURBS) function.

11. The method of claim 1, wherein the radiographic data is an MR image.

12. The method of claim 1, wherein the section function is a predetermined shape.

13. The method of claim 12, wherein the predetermined shape is a circle.

14. The method of claim 13, wherein the radius of the circle is dependent upon a length along the trajectory function.

15. The method of claim 1, wherein the 3D model is a 3D mesh and generating the 3D mesh includes sweeping the section function along the trajectory function.

16. The method of claim 1, wherein constructing the trajectory function includes interpolating a curve of the trajectory function through each of the identified approximate locations of the markers in a particular order.

17. The method of claim 1, wherein constructing the trajectory function includes approximating a curve of the trajectory function by permitting the curve to not intersect each identified approximate locations of the markers and by minimizing a sum of errors calculated as a distance between each identified approximate location of the markers and a corresponding point along the curve.

18. The method of claim 17, wherein identifying an approximate location of each of the plurality of markers within the radiographic data includes determining a confidence or probability for the approximate locations.

19. The method of claim 1, wherein prior to generating the 3D model, it is determined whether he trajectory function is degenerative and where the trajectory function is determined to be degenerative, a warning message is displayed on the display device.

2. The method of claim herein the device is a catheter and the plurality of markers include one or more micro-coils.

3. The method of claim 2, wherein the set of physical characteristics includes distances between adjacent micro-coils of the one or more mico-coils and a measure of maximum possible curvature or bending of the catheter.

20. A method for providing visualization for intervention guidance, comprising:

acquiring a radiographic study;

identifying a set of markers within a device within the acquired radiographic study;

fitting a curve to the identified set of markers according to locations of the identified set of markers within the radiographic study and a prior knowledge of physical characteristics of the device;

generating a 3D model for the device by aligning a deformable model of the device over the fitted curve; and

displaying a rendering of the 3D model on a display device for intervention guidance,

wherein the a prior knowledge of physical characteristics of the device includes distances between markers within the device and a maximum possible degree of curvature or bending of the device.

21. The method of claim 20, wherein the curve is a mathematical spline function defined by a knot vector, a vector of control points, and a degree of polynomial for the spline function and the knot vector and the vector of control points are varied to find a spline function which satisfies one or more constraints of the a prior knowledge of the physical characteristics of the device.

22. The method of claim 20, wherein generating the 3D model for the device includes sweeping a se ion curve along the fitted curve.

23. A computer system comprising:

a processor; and

a non-transitory, tangible, program storage medium, readable by the computer system, embodying a program of instructions executable by the processor to perform method steps for device visualization, the method comprising;

receiving a set of physical characteristics including a description of spatial relationships of a plurality of markers within a device;

acquiring a radiographic scan of the device within a subject;

identifying an approximate location of each of the plurality of markers within the radiographic scan;

constructing a mathematical spline function for the device within the subject based on the identified approximate locations of each of the markers and the received set of physical characteristics;

generating a 3D model for the device based on the constructed spline function; and

displaying a rendering of the 3D model on a display device.