Coregistration and analysis of multi-modal images obtained in different geometries

Patent metadata

Field	Value
Publication number	US-9251585-B2
Application number	US-16908108-A
Country	US
Kind code	B2
Filing date	Jul 8, 2008
Priority date	Jul 12, 2007
Publication date	Feb 2, 2016
Grant date	Feb 2, 2016

Abstract

A method for coregistration of multi-modal images obtained in different geometries includes acquiring multi-modal image data, wherein the multi-model image data includes image data of a first modality and image data of a second modality, wherein the image data of the respective modalities have different geometries, defining a volume of interest in the multi-modal image data, segmenting the image data of the first modality and incorporating segmentation data of the first modality into a reconstruction of the second modality, and applying a registration of the second modality image data to the first modality image data according to a similarity measure through the volume of interest, wherein an output of the registration comprises superimposed multi-modal image data.

First claim

What is claimed is:

1. A non-transitory computer readable medium embodying instructions executable by a processor to perform a method for coregistration of multi-modal images, the method steps comprising:
acquiring multi-modal volumetric image data, wherein the multi-modal volumetric image data includes volumetric image data of a first modality and volumetric image data of a second modality, wherein a same tissue captured in the image data of the first and second modalities has different geometries;
defining a volume of interest in the multi-modal volumetric image data, wherein defining the volume of interest comprises:
determining three mutually orthogonal signatures for the first and the second modalities; and
registering, iteratively, each of the three mutually orthogonal signatures of one of the first and the second modalities to the three mutually orthogonal signatures of the other modality, wherein registered signatures are combined into a 9-dimensional parameter space corresponding to the volume of interest;

segmenting the volumetric image data of the first modality and incorporating priors of segmentation data of the first modality into a reconstruction of the volumetric image data of the second modality; and
applying a registration to transform the second modality volumetric image data to align with the first modality volumetric image data according to a similarity measure through the 9-dimensional parameter space corresponding to the volume of interest, wherein an output of the registration comprises superimposed multi-modal volumetric image data wherein the geometries of the same tissue are aligned.

2. The computer readable medium of claim 1 , wherein the multi-modal volumetric image data is converted into a common binary format.

3. The computer readable medium of claim 1 , wherein the multi-modal volumetric image data is acquired non-concurrently.

4. The computer readable medium of claim 1 , wherein the registration further comprises acquiring multiple two-dimensional projections of the volume of interest.

5. The computer readable medium of claim 4 , wherein the registration is a non-rigid registration determining the similarity according to a measure of a maximum intensity projection of the two-dimensional projections.

6. The computer readable medium of claim 4 , wherein the registration is a non-rigid registration determining the similarity according to a measure of a maximum intensity projection of three mutually orthogonal two-dimensional projections.

7. The computer readable medium of claim 4 , wherein the registration is a non-rigid registration determining the similarity according to a measure of a normalized mutual information of the two-dimensional projections.

8. The computer readable medium of claim 4 , wherein the registration is a non-rigid registration determining the similarity according to a measure of rigid body motion translation and rotation, and independent linear scaling in multiple dimensions of the two-dimensional projections.

9. The computer readable medium of claim 8 , further comprising:
generating a plurality of mutually orthogonal two-dimensional signatures for the first and second modality volumetric image data; and
registering the second modality image data to the first modality image data after each two-dimensional signature is generated.

10. The computer readable medium of claim 1 , wherein the first modality volumetric image data captures anatomical data and the second modality volumetric image data captures functional data of tissue in the volume of interest, wherein the anatomical data is prior information for the reconstruction of the volumetric image data of the second modality.

11. A method for coregistration of multi-modal images comprising:
acquiring multi-modal volumetric image data, wherein the multi-modal volumetric image data includes volumetric image data of a first modality and volumetric image data of a second modality, wherein a same tissue captured in the image data of the first and second modalities has different geometries;
defining a volume of interest in the multi-modal volumetric image data, wherein defining the volume of interest comprises:
determining three mutually orthogonal signatures for the first and the second modalities; and
registering, iteratively, each of the three mutually orthogonal signatures of one of the first and the second modalities to the three mutually orthogonal signatures of the other modality, wherein registered signatures are combined into a 9-dimensional parameter space corresponding to the volume of interest;

segmenting the volumetric image data of the first modality and incorporating priors of segmentation data of the first modality into a reconstruction of the volumetric image data of the second modality; and
applying a registration to transform the second modality volumetric image data to align with the first modality volumetric image data according to a similarity measure through the 9-dimensional parameter space corresponding to the volume of interest, wherein an output of the registration comprises superimposed multi-modal volumetric image data wherein the geometries of the same tissue are aligned.

12. The method of claim 11 , wherein the multi-modal volumetric image data is converted into a common binary format.

13. The method of claim 11 , wherein the multi-modal volumetric image data is acquired non-concurrently.

14. The method of claim 11 , wherein the registration further comprises acquiring multiple two-dimensional projections of the volume of interest.

15. The method of claim 14 , wherein the registration is a non-rigid registration determining the similarity according to a measure of a maximum intensity projection of the two-dimensional projections.

16. The method of claim 14 , wherein the registration is a non-rigid registration determining the similarity according to a measure of a maximum intensity projection of three mutually orthogonal two-dimensional projections.

17. The method of claim 14 , wherein the registration is a non-rigid registration determining the similarity according to a measure of a normalized mutual information of the two-dimensional projections.

18. The method of claim 14 , wherein the registration is a non-rigid registration determining the similarity according to a measure of rigid body motion translation and rotation, and independent linear scaling in multiple dimensions of the two-dimensional projections.

19. The method of claim 18 , further comprising:
generating a plurality of mutually orthogonal two-dimensional signatures for the first and second modality volumetric image data; and
registering the second modality volumetric image data to the first modality volumetric image data after each two-dimensional signature is generated.

20. The method of claim 11 , wherein the first modality volumetric image data captures anatomical data and the second modality volumetric image data captures functional data of tissue in the volume of interest, wherein the anatomical data is prior information for the reconstruction of the volumetric image data of the second modality.

Assignees

• Azar Fred S
• Yodh Arjun G
• Choe Regine
• Lee Kijoon
• Siemens Ag

Inventors

• Azar Fred S
• Yodh Arjun G
• Choe Regine
• Lee Kijoon

Classifications

• G06T7/0081

  Physics · mapped topic

• G01R33/5608

  Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels (image data processing or generation, in general G06T) · CPC title

• G01R33/4808

  Multimodal MR, e.g. MR combined with positron emission tomography [PET], MR combined with ultrasound or MR combined with computed tomography [CT] · CPC title

• G06T7/0038

  Physics · mapped topic

• G06T7/0034 Primary

  Physics · mapped topic