Apparatus and method for registering two medical images

• US 8,620,055 B2
• Filed: 08/05/2010
• Issued: 12/31/2013
• Est. Priority Date: 08/07/2009
• Status: Active Grant

• Current Assignee: UCL Business PLC (University of London)
• Original Assignee: UCL Business PLC (University of London)
• Inventors: Barratt, Dean, Hu, Yipeng
• Primary Examiner(s): Tabatabai, Abolfazl
• Application Number:
  US13/388,932
• Publication Number:
  US 20120155734A1
• Time in Patent Office: 1,244 Days
• Field of Search: 382/128, 382/129, 382/130, 382/131, 382/132, 382/133, 382/134, 382/151, 382/294, 378/4, 378/8, 378 21- 27, 378/101, 378/901, 600/37, 600/407, 600/410, 600/425, 600/437, 601/153, 128/920, 128/922
• US Class Current: 382/131
• 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 2207/10136 3D ultrasound image
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 2207/30081 Prostate
• CPC Class Codes: G06T 7/344 involving models
• CPC Class Codes: G06T 7/35 using statistical methods

Abstract

An embodiment of the invention provides a method and apparatus for registering two medical images with one another. A first medical image including a representation of a biological organ of a subject or for a population is obtained and the surface of the organ is identified in the first medical image. The identified surface is then used to construct a 3D geometric surface model of the organ. The geometric model is used to derive a motion model that incorporates information on the physical material properties of the organ and external forces that cause the organ to move and deform. A second medical image including a representation of the organ of the subject (or another subject, in the case that the first medical image is an atlas image) is obtained and an alignment is determined between a first surface normal vector field for the organ surface, derived from the geometric model, and a second surface normal vector field for the organ surface, derived by filtering the second medical image. The alignment accommodates deformation of the geometric model in accordance with the motion predicted by the motion model. The first and second medical images can then be registered with one another based on said determined model-to-image vector alignment (MIVA).

Claims

1. A method for registering two medical images, said method comprising:

obtaining a first medical image including a patient-specific representation of a biological organ of an individual subject or a representation of a biological organ for a population;

identifying the surface of said organ in said first medical image;

using said surface to obtain a geometric model that represents the three-dimensional shape of said organ for a subject or the representative shape of said organ for a population;

using said geometric model to obtain a motion model which can be used to predict the physical motion and deformation of said organ;

obtaining a second medical image including a representation of said organ of said subject or another subject;

determining an alignment between surface normal vectors of said geometric model, which represent a first vector field, and estimated surface normal vectors of the organ surface derived by filtering said second medical image, which represent a second vector field, wherein determining said alignment includes applying a mathematical transformation to said geometric model to maximise a measure of orientational alignment between the first and second vector fields, and wherein the spatial position, orientation and shape of said geometric model and of said first vector field are changed in accordance with said motion model to achieve said alignment;

and registering the first and second medical images with one another based on said determined alignment.

2. The method of claim 1, wherein the first medical image is a magnetic resonance (MR) image or an X-ray computed tomography (CT) image.

3. The method of claim 1, wherein the first medical image is an ultrasound image or an atlas image.

4. The method of claim 1, wherein the second medical image is an ultrasound image.

5. The method of claim 1, wherein said anatomical feature comprises the prostate gland.

6. The method of claim 1, wherein obtaining said first image, said geometric model and said motion model is performed prior to a time-point in a surgical procedure when determining the alignment between said first image and said second image of a subject undergoing such a procedure is required for the purposes of surgical navigation.

7. The method of claim 6, wherein said geometric model is included as part of a plan for a surgical treatment or a diagnostic test.

8. The method of claim 1, wherein said geometric model is derived using statistical shape modelling techniques.

9. The method of claim 1, wherein said geometric model is a finite element mesh that describes the surface of said organ.

10. The method of claim 9, wherein said finite element mesh is generated from a spherical harmonic representation of said identified surface.

11. The method of claim 1, wherein constructing said motion model further includes using solid modelling tools to generate a volumetric finite element model from said geometric model.

12. The method of claim 11, wherein constructing said motion model further includes using finite element analysis to determine the displacement of the mesh nodes (vertices) of said finite element model, and assigning physical material properties to the model in accordance with the physiological ranges of such properties.

13. The method of claim 12, further comprising the use of finite element analysis to perform a set of simulations, said simulations representing various physically plausible deformations of said organ.

14. The method of claim 13, further comprising performing statistical analysis of the displacements of said finite element mesh nodes (vertices) calculated by said simulations to generate the motion model for the organ.

15. The method of claim 1, wherein determining the alignment includes an initialisation step of identifying one or more points corresponding to anatomical landmarks in the second medical image and matching them to said geometric model in order to approximately orientate the geometric model with respect to the second medical image.

16. The method of claim 1, wherein said first vector field comprises a three-dimensional vector field in which each vector has a location corresponding to a point on the surface of said geometric model and an orientation normal to said surface of said geometric model.

17. The method of claim 1, wherein said filtering of said second medical image is based on an eigenanalysis of the second order Gaussian derivatives of the voxel (3D pixel) intensity values of said image to determine said second vector field of surface normal vectors.

18. The method of claim 1, wherein said second vector field, derived by filtering said second medical image, is considered to be a noise-corrupted version of the first vector field.

19. The method of claim 18, wherein said alignment is determined on the basis of maximising the joint probability of the noise.

20. The method of claim 1, wherein said alignment is determined using a vector similarity measure that quantifies the orientational alignment between said first and second vector fields by calculating a function of the inner product of estimated surface normal vectors in said second vector field and surface normal vectors in said first vector field after being transformed into a local co-ordinate system of said second image.

21. The method of claim 20, wherein said vector similarity measure accounts for the presence of artefacts dependent on ultrasound beam direction when said image is an ultrasound image.

22. The method of claim 1, wherein determining said alignment includes re-positioning and deforming said geometric model such that the final shape and position of the deformed model provides a best fit to the organ surface in the co-ordinate system of said second medical image.

23. The method of claim 22, wherein registering the first and second medical images with one another based on said determined alignment includes calculating a dense displacement field comprising displacements that map from said geometric model to said deformed geometric model.

24. A non-transitory computer readable storage medium storing computer program instructions for execution by a processor in an apparatus for causing the apparatus to implement a method for registering two medical images comprising:

obtaining a first medical image including a patient-specific representation of a biological organ of an individual subject or a representation of a biological organ for a population;

identifying the surface of said organ in said first medical image;

using said surface to obtain a geometric model that represents the three-dimensional shape of said organ for a subject or the representative shape of said organ for a population;

using said geometric model to obtain a motion model which can be used to predict the physical motion and deformation of said organ;

obtaining a second medical image including a representation of said organ of said subject or another subject;

determining an alignment between surface normal vectors of said geometric model, which represent a first vector field, and estimated surface normal vectors of the organ surface derived by filtering said second medical image, which represent a second vector field, wherein determining said alignment includes applying a mathematical transformation to said geometric model to maximise a measure of orientational alignment between the first and second vector fields, and wherein the spatial position, orientation and shape of said geometric model and of said first vector field are changed in accordance with said motion model to achieve said alignment;

and registering the first and second medical images with one another based on said determined alignment.

25. Apparatus for registering two medical images, comprising:

an image processing system for identifying an organ surface in a first medical image that includes a representation of the said organ;

a modelling system for using the identified surface to construct a 3D geometric model of said organ surface;

a modelling system for constructing said organ motion model from said 3-D geometric model;

an image processing system for calculating first and second surface normal vector fields from said geometric model and from said second medical image respectively;

a numerical optimisation system for determining an alignment between said first vector field and said second vector field, wherein determining said alignment includes applying a mathematical transformation to said geometric model to maximise a measure of orientational alignment between the first and second vector fields, and wherein the spatial position, orientation and shape of said geometric model and of said first vector field are changed in accordance with said motion model to achieve said alignment, thereby accommodating deformation of the geometric model in accordance with said motion model; and

an image registration system for registering the first and second medical images with one another based on said determined alignment.

26. The apparatus of claim 25, further comprising an image fusion system for visualising the first and second medical images together based on said determined alignment.