Method and system for calculating a displacement of an object of interest

• US 10,346,989 B2
• Filed: 12/11/2015
• Issued: 07/09/2019
• Est. Priority Date: 12/17/2014
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: Xu, Jingping, Lu, Kongkuo, Shi, William Tao, Hall, Christopher Stephen
• Primary Examiner(s): Desire, Gregory M
• Application Number:
  US15/535,763
• Publication Number:
  US 20170345158A1
• Time in Patent Office: 1,306 Days
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/248 involving reference images or patches
• CPC Class Codes: G06T 7/38 Registration of image sequences

Abstract

The invention relates to a method of calculating a displacement of an object of interest comprising a step of calculating (101) a displacement model of said object of interest from adjacent images of a set of pre-acquired images of said object of interest, said displacement model reflects the position of said object of interest along the time. The method is characterized in that the method further comprises the following. A step of determining (102) a first sub-set of images (S1) from said set of pre acquired images within one periodical time cycle of said set of pre-acquired images on the basis of the displacement model. A first step of identifying (103) a second sub-set of images (S2) from newly-acquired images, wherein images in said second sub-set of images (S2) are consecutive and have the same most similar image in said first sub-set of images (S1), wherein a first set of similarity levels is determined by comparing a given image in said newly acquired images with each image of said first sub-set of images (S1), and wherein said most similar image has the largest similarity level in said first set of similarity levels. A first step of selecting (104) a given image in said second sub-set of images (S2) as a first reference image (I1). A second step of identifying (105) a third sub-set of images (S3) from said newly-acquired images, wherein images in said third sub-set of images (S3) are consecutive and have the same most similar image in said first sub-set of images (S1), wherein a set of similarity levels is determined by comparing a given image in said newly acquired images with each image of said first sub-set of images (S1), and wherein said most similar image has the largest similarity level in said set of similarity levels. A second step of selecting (106) a given image in said third sub-set of images (S3) as a second reference image (I2). A step of calculating (107) the displacement between said second reference image (I2) and said first reference image (I1). The invention also relates to a corresponding system of displacement calculation.

Claims

1. A method of calculating a displacement of an object of interest, comprising a step of calculating, with a processor, a displacement model of said object of interest from adjacent images of a set of pre-acquired images of said object of interest, said displacement model being periodical and reflecting the position of said object of interest along the time, characterize in that said method further comprising:

a step of determining, with the processor, a first sub-set of images from said set of pre-acquired images within one periodical time cycle of said set of pre-acquired images on the basis of the displacement model;

a first step of identifying, with the processor, a second sub-set of images from newly-acquired images, wherein images in said second sub-set of images are consecutive and have the same most similar image in said first sub-set of images, wherein a set of similarity levels is determined by comparing a given image in said newly acquired images with each image of said first sub-set of images, and wherein said most similar image has the largest similarity level in said set of similarity levels;

a first step of selecting, with the processor, a given image in said second sub-set of images as a first reference image;

a second step of identifying, with the processor, a third sub-set of images from said newly-acquired images, wherein images in said third sub-set of images are consecutive and have the same most similar image in said first sub-set of images, wherein a set of similarity levels is determined by comparing a given image in said newly acquired images with each image of said first sub-set of images, wherein said most similar image has the largest similarity level in said set of similarity levels, and wherein the same most similar image which the images in the third sub-set of images have is different from the same most similar image which the images in the second sub-set of images have;

a second step of selecting with the processor, a given image in said third sub-set of images as a second reference image;

a step of calculating, with the processor, the displacement between said second reference image and said first reference image.

2. A method as claimed in claim 1, wherein said step of determining is adapted to determining said first sub-set of images having a number of images chosen in the set.

3. A method as claimed in claim 1, wherein said step of determining comprises selecting a first region and a second region within a periodical time cycle of said displacement model, wherein the number of images selected in said first region is larger than the number of images selected in said second region, and wherein the slope of said displacement model within said first region is larger than the slope of said displacement model within said second region.

4. A method as claimed in claim 1, wherein after said step of determining, further comprising a step of attaching indicators to said first sub-set of image, said indicators comprising respiratory expiration information and respiratory inspiration information of said object of interest.

5. A method as claimed in claim 4, wherein said first step of identifying comprises the sub-steps of:

attaching an indicator to a newly acquired image based on comparing with the consecutive image, wherein said indicator comprising respiratory expiration information and respiratory inspiration information;

identifying a fourth sub-set of images from said first sub-set of images, wherein said fourth sub-set of images have the same indicator;

identifying said second sub-set of images from newly acquired images, wherein images in said second sub-set of images have the same most similar image in said fourth sub-set of images.

6. A method as claimed in claim 4, wherein said second step of identifying comprises the sub-steps of:

attaching an indicator to a newly acquired image based on comparing with the adjacent image, wherein said indicator comprising respiratory expiration information and respiratory inspiration information;

identifying a fourth sub-set of images from said first sub-set of images, wherein said fourth sub-set of images have the same indicator;

identifying said third sub-set of images from newly acquired images, wherein images in said third sub-set of images have the same most similar image in said fourth sub-set of images.

7. A method as claimed in claim 1, wherein the most similar image in said first step of identifying and in said second step of identifying is identified based on using criteria chosen among volume-to-volume cross-correlation criteria and minim of sum of square difference criteria.

8. A method as claimed in claim 1, wherein said first step of selecting comprises selecting said first reference image in a central time slot of said newly acquired images.

9. A method as claimed in claim 1, wherein said second step of selecting comprises selecting said second reference image in a central time slot of said newly acquired images.

10. A method as claimed in claim 1, further comprising:

a sub-step of compensating, based on said displacement, the position of a radiation beam intended to be directed to said object of interest.

11. A system for calculating a displacement, said system comprising a processor configured to calculate a displacement model of said object of interest from adjacent images of a set of pre-acquired images of said object of interest, said displacement model being periodical and reflecting the position of said object of interest along the time, characterize in that said processor is further configured to:

determine a first sub-set of images from said set of pre-acquired images within one periodical time cycle of said set of pre-acquired images on the basis of the displacement model;

identify a second sub-set of images from newly-acquired images, wherein images in said second sub-set of images are consecutive and have the same most similar image in said first sub-set of images, wherein a set of similarity levels is determined by comparing a given image in said newly acquired images with each image of said first sub-set of images, and wherein said most similar image has the largest similarity level in said set of similarity levels;

select a given image in said second sub-set of images as a first reference image;

identify a third sub-set of images from said newly-acquired images, wherein images in said third sub-set of images are consecutive and have the same most similar image in said first sub-set of images, wherein a set of similarity levels is determined by comparing a given image in said newly acquired images with each image of said first sub-set of images wherein said most similar image has the largest similarity level in said set of similarity levels, and wherein the same most similar image which the images in the third sub-set of images have is different from the same most similar image which the images in the second sub-set of images have;

select a given image in said third sub-set of images as a second reference image; and

calculate the displacement between said second reference image and said first reference image.

12. A system as claimed in claim 11, adapted to connect to an image acquisition module for acquiring images of said object of interest.

13. A system as claimed in claim 12, wherein said image acquisition module is an ultrasound imaging acquisition module.

14. A system as claimed in claim 11, adapted to connect to a control module of a radiation therapy equipment, and to send the calculated displacement to the control module.