Three dimensional (3D) pre-scan based volumetric image data processing

• US 10,045,754 B2
• Filed: 11/25/2014
• Issued: 08/14/2018
• Est. Priority Date: 12/11/2013
• Status: Expired due to Fees

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: Klinder, Tobias, Lorenz, Cristian, Bergtholdt, Martin, Wiemker, Rafael
• Primary Examiner(s): BHATNAGAR, ANAND P
• Application Number:
  US15/102,554
• Publication Number:
  US 20160310090A1
• Time in Patent Office: 1,358 Days
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 6/03 Computed tomography [CT] echo-tomography A61B8/14
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/037 Emission tomography
• CPC Class Codes: A61B 6/488 involving pre-scan acquisition
• CPC Class Codes: A61B 6/50 specially adapted for specific body parts; specially adapted for specific clinical applications
• CPC Class Codes: A61B 6/5235 combining images from the same or different ionising radiation imaging techniques, e.g. PET and CT
• CPC Class Codes: A61B 6/5264 due to motion
• CPC Class Codes: A61B 6/5288 involving retrospective matching to a physiological signal
• CPC Class Codes: A61B 6/541 involving acquisition triggered by a physiological signal
• CPC Class Codes: G01R 33/543 Control of the operation of the MR system, e.g. setting of acquisition parameters prior to or during MR data acquisition, dynamic shimming, use of one or more scout images for scan plane prescription G01R33/546 takes precedence
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/20201 Motion blur correction
• CPC Class Codes: G06T 2207/20221 Image fusion; Image merging
• CPC Class Codes: G06T 3/4038 Image mosaicing, e.g. composing plane images from plane sub-images
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening
• CPC Class Codes: G06T 7/0014 using an image reference approach
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/30 Determination of transform parameters for the alignment of images, i.e. image registration
• CPC Class Codes: G06T 7/37 : using transform domain methods

Abstract

A method includes determining a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The method further includes registering first volumetric scan image data and second volumetric scan image data based on the registration transform. The method further includes generating registered image data. A system (100) includes a pre-scan registerer (122) that determines a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The system further includes a volume registerer (126) that registers first volumetric scan image data and second volumetric scan image data based on the registration transform, generating registered image data.

Claims

1. A method, comprising:

determining a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm; and

registering first volumetric scan image data and second volumetric scan image data based on the registration transform, generating registered image data,

wherein a field of view of the first volumetric scan image data is less than a field of view of the first three dimensional pre-scan image data, and a field of view of the second volumetric scan image data is less than a field of view of the second three dimensional pre-scan image data.

2. The method of claim 1, wherein the first volumetric scan image data is acquired with a first scan plan determined based on the first three dimensional pre-scan image data, and the second volumetric scan image data is acquired with a second scan plan determined based on the second three dimensional pre-scan image data.

3. The method of claim 1, wherein the first three dimensional pre-scan image data and the second three dimensional pre-scan image data are acquired with a lower patient dose than the first volumetric scan image data and the second volumetric scan image data.

4. The method of claim 1, wherein the first three dimensional pre-scan image data and the second three dimensional pre-scan image data have a lower image quality than the first volumetric scan image data and the second volumetric scan image data.

5. The method of claim 2, further comprising:

determining the first scan plan by identifying a first scan start location and a first scan end location in the first three dimensional pre-scan image data;

performing the first scan plan, thereby generating the first volumetric scan image data;

determining the second scan plan by identifying a second scan start location and a second scan end location in the second three dimensional pre-scan image data; and

performing the second scan plan, thereby generating the second volumetric scan image data.

6. The method of claim 1, wherein a field of view of the first volumetric scan image data is a sub-set of a field of view of the first three dimensional pre-scan image data, and a field of view of the second volumetric scan image data is a sub-set of a field of view of the second three dimensional pre-scan image data.

7. The method of claim 1, wherein the field of view of the first volumetric scan image data and the field of view of the second volumetric scan image data are not a same field of view.

8. The method of claim 7, further comprising:

adding a sub-portion of the first three dimensional pre-scan image data to the first volumetric scan image data and a sub-portion of the second three dimensional pre-scan image data to the second volumetric scan image data, creating extended first volumetric scan image data and extended second volumetric scan image data.

9. The method of claim 8, wherein the extended first volumetric scan image data and the extended second volumetric scan image data have a same extended field of view.

10. The method of claim 8, further comprising:

registering the extended first volumetric scan image data and the extended second volumetric scan image data based on the registration transform, generating the registered image data.

11. The method of claim 1, wherein the first three dimensional pre-scan image data and the second three dimensional pre-scan image data are acquired at a first motion state and the first volumetric scan image data and the second volumetric scan image data are acquired at a second, different motion state, and further comprising:

determining a first motion vector field for the first volumetric scan image data based on the first volumetric scan image data and the first three dimensional pre-scan image data;

determining a second motion vector field for the second volumetric scan image data based on the second volumetric scan image data and second three dimensional pre-scan image data;

motion compensating the first volumetric scan image data based on the first motion vector;

motion compensating the second volumetric scan image data based on the second motion vector; and

registering the motion compensated first volumetric scan image data and the motion compensated second volumetric scan image data based on the registration transform, generating the registered image data.

12. The method of claim 11, wherein the first motion state is respiratory inhale and the second motion state is respiratory exhale or vice-versa.

13. The method of claim 11, further comprising:

employing the first motion vector field to modify a general motion model, thereby creating a first subject-specific motion model;

employing the second motion vector field to modify the general motion model, thereby creating a second subject-specific motion model;

motion compensating the first volumetric scan image data based on the first subject-specific motion model;

motion compensating the second volumetric scan image data based on the second subject-specific motion model; and

registering the motion compensated first volumetric scan image data and the motion compensated second volumetric scan image data based on the registration transform, generating the registered image data.

14. A system, comprising:

a processor, including;

a pre-scan registerer that determines a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm;

determining a first motion vector field for first volumetric scan image data based on the first volumetric scan image data and the first three dimensional pre-scan image data; and

motion compensating the first volumetric scan image data based on the first motion vector field; and

a volume registerer that registers the motion compensated first volumetric scan image data and second volumetric scan image data based on the registration transform, generating registered image data.

15. The system of claim 14, wherein the first volumetric scan image data is acquired with a first scan plan determined based on the first three dimensional pre-scan image data, and the second volumetric scan image data is acquired with a second scan plan determined based on the second three dimensional pre-scan image data.

16. The system of claim 14, wherein the first three dimensional pre-scan image data and the second three dimensional pre-scan image data are acquired with a lower patient dose than the first volumetric scan image data and the second volumetric scan image data.

17. The system of claim 14, wherein a field of view of the first volumetric scan image data and a field of view of the second volumetric scan image data are not a same field of view, and the processor further comprising:

a field of view combiner that combines the field of view of the first volumetric scan image data and the field of view of the second volumetric scan image data, producing a combined field of view of the first and the second volumetric scan image data, wherein the combined field of view is greater than either of the field of view of the first volumetric scan image data and the field of view of the second volumetric scan image data;

a missing image data identifier that identifies a first sub-portion of the combined field of view that is not part of the field of view of the first volumetric scan image data and a second sub-portion of the combined field of view that is not part of the field of view of the second volumetric scan image data;

an image data extractor that extracts the identified first and second sub-portions respectively in the first three dimensional pre-scan image data and the second three dimensional pre-scan image data; and

an image data extender that extends the first volumetric scan image data with the extracted identified first sub-portion and that extends the second volumetric scan image data with the extracted identified second sub-portion.

18. The system of claim 14, wherein the second three dimensional pre-scan image data is acquired at the first motion state and the second volumetric scan image data is acquired at the second, different motion state, and the processor further comprising:

determining a second motion vector field for the second volumetric scan image data based on the second volumetric scan image data and second three dimensional pre-scan image data;

motion compensating the second volumetric scan image data based on the second motion vector field; and

registering the motion compensated first volumetric scan image data and the motion compensated second volumetric scan image data based on the registration transform, generating the registered image data.

19. A method, comprising:

combining 3D pre-scan image data with volumetric image data from a volume scan, wherein the 3D pre-scan image data was used to plan the volume scan, generating combined image data;

segmenting tissue of interest from the volumetric image data based on the combined image data; and

visually displaying the segmented volumetric image data.

20. The method of claim 19, wherein the 3D pre-scan image data has a first image contrast resolution and the volumetric image data has a second image contrast resolution, and the first image contrast resolution is lower than the second image contrast resolution.

21. The method of claim 19, further comprising:

segmenting a volumetric image data sub-portion of the combined image data using a higher resolution segmentation algorithm; and

segmenting a 3D pre-scan image data sub-portion of the combined image data using a lower resolution segmentation algorithm.

22. The method of claim 21, wherein the segmenting includes combining the organ and combining the sub-portion of the at least one neighboring organ.

23. The method of claim 19, wherein the tissue of interest is an organ, the volumetric image data includes the entire organ, and the 3D pre-scan image data includes at least a sub-portion of at least one neighboring organ.

24. A system, comprising:

a processor, including;

a combiner that combines 3D pre-scan image data with volumetric image data from a volume scan, wherein the 3D pre-scan image data was used to plan the volume scan, generating combined image data; and

a segmentor that segments tissue of interest from the volumetric image data based on the combined image data,

wherein the 3D pre-scan image data has a first image contrast resolution and the volumetric image data has a second image contrast resolution, and the first image contrast resolution is lower than the second image contrast resolution.

25. The system of claim 24, wherein the segmentor segments a volumetric image data sub-portion of the combined image data using a higher resolution segmentation algorithm and segments a 3D pre-scan image data sub-portion of the combined image data using a lower resolution segmentation algorithm.

26. The system of claim 24, wherein the tissue of interest is an organ, the volumetric image data includes the entire organ, and the 3D pre-scan image data includes at least a sub-portion of at least one neighboring organ.

27. The system of claim 24, wherein the segmentor segments the organ and segments the sub-portion of at least one neighboring organ.