IP Library Granted Patent US 10,269,115
Granted Patent B2
US 10,269,115 · App. 15/325,102 · Granted Apr 23, 2019

Imaging data statistical testing including a stereotactical normalization with a personalized template image

Inventors: Fabian Wenzel (Hamburg, DE); Stewart Young (Hamburg, DE)
Assignee: KONINKLIJKE PHILIPS N.V.
G06T7/0012G06T7/30G06T11/60G06T2207/10104G06T2207/20128G06T2207/30016
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Quick Facts
Patent No.
US 10,269,115
App. No.
15/325,102
Granted
Apr 23, 2019
Kind
B2
Abstract

A method includes obtaining an image of a subject to process via statistical testing. The method further includes obtaining a subject personalized template image, which is personalized to the subject based on a predetermined characteristic of the subject. The method further includes registering the subject personalized template image to the image of the subject. The method further includes performing statistical testing using the subject personalized template image registered to the image of the subject. A computing system ( 304 ) includes a memory ( 320 ) that stores a statistical testing module ( 320 ) and data ( 324 ). The computing system further includes a processor ( 318 ) that executes the one or more instructions, which causes the processor to: perform voxel-wise statistical testing of a functional image using a subject personalized template image for stereotactical normalization of the voxel-wise statistical testing.

Claims (49)

1. A method, comprising:

obtaining a positron emission tomography (PET) image of a subject to process via statistical testing;

dynamically identifying a subject personalized template image based on a predetermined characteristic of the subject;

registering the subject personalized template image to the PET image of the subject to create a stereotactically normalized functional image; and

performing statistical testing using the stereotactically normalized functional image.

2. The method of claim 1 , wherein the predetermined characteristic of the subject is at least one of information external to the image of the subject or information contained in the image of the subject.

3. The method of claim 1 , wherein the predetermined characteristic of the subject is at least one of an age of the subject or a size of a predetermined anatomical tissue type of the subject.

4. The method of claim 1 , further comprising:

selecting the subject personalized template image from a plurality of template images corresponding to different ages.

5. The method of claim 4 , further comprising:

generating an age-based template image by determining an average image from a set of images of subjects of the age or within a predetermined range including the age.

6. The method of claim 1 , further comprising:

generating the subject personalized template image based on a general template image and an age-based transformation corresponding to the age of the patient.

7. The method of claim 1 , further comprising:

selecting the subject personalized template image from a plurality of template images corresponding to different anatomical tissue types.

8. The method of claim 7 , further comprising:

selecting the subject personalized template image by matching a size of the anatomical tissue type in the functional image with a size of the anatomical tissue type in each of a plurality of templates, determining a residual deformation for each match, and selecting the template image which results in a smallest residual deformation.

9. The method of claim 7 , further comprising:

generating a size-based template image template by determining an average image from a set of images of subjects having an anatomical tissue type size within a predetermined size range.

10. The method of claim 1 , wherein the PET image is a brain image.

11. The method of claim 1 , further comprising:

intensity scaling the stereotactically normalized functional image using an intensity reference image;

filtering the intensity scaled, stereotactically normalized functional image;

performing a voxel-wise statistical test on the filtered, intensity scaled, stereotactically normalized functional image, using a normal collective; and

generating a statistical map based on a result of the voxel-wise statistical test.

12. The method of claim 11 , further comprising:

visually displaying the filtered, intensity scaled, stereotactically normalized functional image with the statistical map superimposed thereover.

13. The method of claim 11 , further comprising:

generating a signal indicating the functional image is a candidate image for updating the normal collective in response to the statistical map indicating the subject does not have neuro-degenerative disease.

14. The method of claim 1 , wherein the personalized template image mitigates at least one of stretching artifact or false hypo-metabolism detection.

15. A computing system, comprising:

a memory that stores a statistical testing module and data; and

a processor that executes the one or more instructions, which causes the processor to:

dynamically identify a subject personalized template image based on a predetermined characteristic of the subject;

register the subject personalized template image to a PET functional image of the subject to create a stereotactically normalized functional image; and

perform voxel-wise statistical testing of the PET functional image using the stereotactically normalized functional image.

16. The computing system of claim 15 , wherein the executing of the one or more instructions further causes the processor to:

select an age-based template image from a plurality of template images corresponding to different ages or age ranges based on an age of the subject and perform the voxel-wise statistical testing of the functional image using the selected age-based template image for the stereotactical normalization.

17. The computing system of claim 15 , wherein the executing of the one or more instructions further causes the processor to:

generate an age-based template image from a plurality of age-based transformation corresponding to different ages or age ranges and a general template image, based on an age of the subject, and perform the voxel-wise statistical testing of the functional image using the generated age-based template image for the stereotactical normalization.

18. The computing system of claim 15 , wherein the executing of the one or more instructions further causes the processor to:

select an anatomical tissue type size-based template image from a plurality of template images corresponding to different anatomical tissue type sizes and perform the voxel-wise statistical testing of the functional image using the selected size-based template image for the stereotactical normalization.

19. The computing system of claim 15 , wherein the executing of the one or more instructions further causes the processor to:

generate a statistical map based on a result of the voxel-wise statistical testing; and

visually display the functional map with the statistical map superimposed thereover.

20. A computer readable storage medium encoded with one or more computer executable instructions, which, when executed by a processor of a computing system, causes the processor to:

dynamically identify a subject personalized template image for a stereotactical normalization step of a voxel-wise statistical testing of a PET functional image of the subject, wherein the subject personalized template image is based on at least one of an age of the subject or a size of anatomical tissue of interest of the subject; and

register the subject personalized template image to the PET functional image of the subject to create a stereotactically normalized functional image; and

perform a voxel-wise statistical testing of the PET functional image using the stereotactically normalized functional image for the stereotactical normalization step.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 10, 2017
From: WENZEL, FABIAN; YOUNG, STEWART
To: KONINKLIJKE PHILIPS N.V.
Reel/Frame 040913/0176 →
Continuity (2)
Provisional Application 62024488 · Jul 15, 2014
Related Publication 20170186155A1 · Jun 29, 2017