Method for post-processing a three-dimensional image data set of vessel structure

• US 7,903,856 B2
• Filed: 09/18/2007
• Issued: 03/08/2011
• Est. Priority Date: 09/26/2006
• Status: Active Grant

• Current Assignee: Siemens Healthcare GMBH (Siemens AG)
• Original Assignee: Siemens AG
• Inventors: Pfister, Marcus, Redel, Thomas
• Primary Examiner(s): Tucker; Wesley
• Assistant Examiner(s): Bitar; Nancy
• Application Number:
  US11/901,674
• Publication Number:
  US 20080212857A1
• Time in Patent Office: 1,267 Days
• Field of Search: 382/128, 382/131, 382/266, 382/129, 382/294, 382/276, 382/154, 382/134, 382/130, 345/419, 345/424, 372/62, 372/19, 128/916, 128/920, 128/922, 600/410, 600/423, 600/427
• US Class Current: 382/128
• CPC Class Codes: A61B 2017/00778 Operations on blood vessels A61B2017/22097, A61B2017/320741 take precedence
• CPC Class Codes: A61B 2090/364 Correlation of different images or relation of image positions in respect to the body
• CPC Class Codes: A61B 2090/376 using X-rays, e.g. fluoroscopy
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/481 involving the use of contrast agents
• CPC Class Codes: A61B 6/504 for diagnosis of blood vessels, e.g. by angiography
• CPC Class Codes: A61B 90/36 Image-producing devices or illumination devices not otherwise provided for
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/10116 X-ray image
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06T 7/30 Determination of transform parameters for the alignment of images, i.e. image registration
• CPC Class Codes: Y10S 378/901 Computer tomography program or processor

Abstract

The invention relates to a method for post-processing a 3D image data set of a vessel structure of a human or animal body, in which a 2D DSA (Digital Subtraction Angiography) of the vessel structure is recorded and registered with the 3D image data set. The 2D DSA is compared with a corresponding projection image computed from the 3D data set and this is changed, e.g. by changing the segmentation parameters, to adapt it to the 2D DSA. This enables the outstanding local resolution of the 2D DSA to be used for improving the 3D image data set.

Claims

1. A method for post-processing a 3D image data set of a vessel structure of a live body, comprising:

recording a 2D digital subtraction angiography of the vessel structure in a first direction of projection;

segmenting the 3D image data set and the 2D digital subtraction angiography through a threshold value method with the segments being assigned to the vessel structure;

registering the 2D digital subtraction angiography with the 3D image data set;

generating a computed projection image by computing a projection of the 3D image data set on an image plane in the first direction of projection;

comparing the computed projection image with the 2D digital subtraction angiography;

and automatically modifying a local segmentation threshold value of the 3D image data set for adapting the computed projection image to the 2D digital subtraction angiography;

comparing the segments on the computed projection image and on the 2D digital subtraction angiography to detect a difference area,

assigning the different segment area into a vessel section in the 3D image data set by back projecting the computed projection image, and

changing the local segmentation threshold value of the 3D image data set in the different segment area voxel-by-voxel so that a segment assigned to the vessel section on a further computed projection image closely matches a segment assigned to the vessel section on the 2D digital subtraction angiography.

2. The method as claimed in claim 1, wherein the local segmentation threshold value is spatially smoothed changed voxel-by-voxel before computing the further computed projection image.

3. The method as claimed in claim 1, wherein the local segmentation threshold value is changed voxel-by-voxel so that a segment boundary between the vessel section and a background shifts.

4. The method as claimed in claim 1, wherein a second 2D digital subtraction angiography of the vessel structure is recorded in a second direction of projection.

5. The method as claimed in claim 4, wherein the steps of segmenting, registering, generating, comparing, and modifying are repeated with the second 2D digital subtraction angiography on the second direction of projection.

6. The method as claimed in claim 4, wherein the second direction of projection is at an angle of 30°

to 110°

to the first direction of projection.

7. The method as claimed in claim 1, wherein a plurality of 2D digital subtraction angiographys of the vessel structure are recorded in a plurality of projection directions.

8. The method as claimed in claim 7, wherein the steps of segmenting, registering, generating, comparing, and modifying are repeated with the plurality of 2D digital subtraction angiographys on the corresponding plurality of projection directions.

9. The method as claimed in claim 1, wherein the vessel structure is a cerebral vessel structure.

10. The method as claimed in claim 1, wherein the 2D digital subtraction angiographys is recorded by a C-arm x-ray device.

11. The method as claimed in claim 1, wherein the 3D image data set is recorded by magnetic resonance tomography or computer tomography.

12. The method as claimed in claim 1, wherein the 3D image data set is recorded by 3D rotation angiography and the 2D digital subtraction angiographys is at least partly recorded during the recording of the 3D rotation angiography.

13. The method as claimed in claim 1, wherein the segments are assigned to a background of the 3D image data set.

14. A medical system for post-processing a 3D image data set of a vessel structure of a live body, comprising:

a computing device that;

segments the 3D image data set and a 2D digital subtraction angiography of the vessel structure in a first direction of projection through a threshold value method with the segments being assigned to the vessel structure,

registers the 2D digital subtraction angiography with the 3D image data set,

generates a computed projection image by computing a projection of the 3D image data set on an image plane in the first direction of projection

compares the computed projection image with the 2D digital subtraction angiography, and automatically modifies a local segmentation threshold value of the 3D image data set for adapting the computed projection image to the 2D digital subtraction angiography;

comparing the segments on the computed projection image and on the 2D digital subtraction angiography to detect a difference area,

assigning the different segment area into a vessel section in the 3D image data set by back projecting the computed projection image, and

changing the local segmentation threshold value of the 3D image data set in the different segment area voxel-by-voxel so that a segment assigned to the vessel section on a further computed projection image closely matches a segment assigned to the vessel section on the 2D digital subtraction angiography.