Method and system for obtaining a sequence of x-ray images using a reduced dose of ionizing radiation

Patent metadata

Field	Value
Publication number	US-9259200-B2
Application number	US-201213654714-A
Country	US
Kind code	B2
Filing date	Oct 18, 2012
Priority date	Oct 18, 2012
Publication date	Feb 16, 2016
Grant date	Feb 16, 2016

Abstract

Methods, systems, and apparatus for obtaining a sequence of x-ray images are disclosed. An object of interest in a first x-ray image is detected and an area of interest, based on a predicted motion of the object of interest, is determined. A second x-ray image of the area of interest is acquired using spatial x-ray modification to control an x-ray to pass through a portion of a patient corresponding to the area of interest.

First claim

What is claimed is:

1. A method for obtaining a sequence of x-ray images, comprising:
detecting an object of interest in a patient in a first x-ray image;
determining an area of interest based on a predicted motion of the object of interest;
acquiring a second x-ray image based on the area of interest determined in the first x-ray image using spatial x-ray modification to control an x-ray to pass through a portion of the patient corresponding to the area of interest, the second x-ray image having a reduced imaging size of the patient relative to the first x-ray image;
determining whether the object of interest was successfully detected in the second x-ray image; and
in response to determining that the object of interest was not successfully detected in the second x-ray image:
generating an x-ray scatter image of a region beyond the area of interest determined in the first x-ray image.

2. The method of claim 1 , wherein detecting an object of interest in a first x-ray image comprises:
automatically detecting the object of interest in the first x-ray image using a probabilistic boosting tree (PBT) trained on annotated training data.

3. The method of claim 2 , wherein detecting an object of interest in a first x-ray image further comprises:
determining at least one low probability region of the first x-ray image based on information related to a guidance path of the object of interest; and
removing the determined at least one low probability region from a search space of the PBT prior to automatically detecting the object of interest in the first x-ray image using the PBT.

4. The method of claim 2 , wherein detecting an object of interest in a first x-ray image further comprises:
applying a steerable filter to the first x-ray image to identify at least one high contrast region of the first x-ray image; and
removing the identified at least one high contrast region from a search space of the PBT prior to automatically detecting the object of interest in the first x-ray image using the PBT.

5. The method of claim 1 , wherein determining an area of interest based on a predicted motion of the object of interest comprises:
predicting a next location of the object of interest by predicting a motion of the object of interest; and
defining the area of interest as a region surrounding the predicted next location of the object of interest.

6. The method of claim 5 , wherein predicting a next location of the object of interest by predicting a motion of the object of interest comprises:
predicting the motion of the object of interest using one of: an Extended Kalman Filter model, a Particle Filter model, and a Learnt Motion model.

7. The method of claim 6 , wherein the one of the Extended Kalman Filter model, the Particle Filter model, and the Learnt Motion model incorporates prior information regarding a planned path of the object of interest.

8. The method of claim 1 , wherein acquiring a second x-ray image of the area of interest using spatial x-ray modification to control an x-ray to pass through a portion of a patient corresponding to the area of interest comprises:
changing at least one collimator of an imaging device to alter at least one of a shape and a position of an x-ray lightbeam, such that the x-ray lightbeam only passes through the portion of the patient corresponding to the area of interest.

9. The method of claim 1 , wherein acquiring a second x-ray image of the area of interest comprises:
utilizing at least one semitransparent collimator of the image device to constrain the x-ray lightbeam to only pass through the portion of the patient corresponding to the area of interest.

10. The method of claim 1 , wherein acquiring a second x-ray image of the area of interest comprises:
changing at least one of an angulation of a C-arm of the imaging device and a rotation of a detector of the imaging device.

11. The method of claim 1 , wherein acquiring a second x-ray image of the area of interest comprises:
changing a position of a table of the imaging device.

12. The method of claim 1 , further comprising:
detecting the object of interest in the second x-ray image;
determining a second area of interest based on a second predicted motion of the object of interest detected in the second x-ray image; and
acquiring a third x-ray image of the second area of interest using spatial x-ray modification to control an x-ray to pass through a portion of the patient corresponding to the second area of interest.

13. The method of claim 1 , further comprising:
in response to determining that the object of interest was not successfully detected in the second x-ray image:
detecting the object of interest in the x-ray scatter image.

14. The method of claim 13 , wherein detecting the object of interest in the x-ray scatter image comprises:
detecting the object of interest in the x-ray scatter image using a probabilistic boosting tree (PBT) trained on annotated training data comprising x-ray scatter image data.

15. A non-transitory computer readable medium storing computer program instructions for obtaining a sequence of x-ray images, which, when the instructions are executed on a processor, cause the processor to perform operations comprising:
detecting an object of interest in a patient in a first x-ray image;
determining an area of interest based on a predicted motion of the object of interest;
acquiring a second x-ray image based on the area of interest determined in the first x-ray image using spatial x-ray modification to control an x-ray to pass through a portion of the patient corresponding to the area of interest, the second x-ray image having a reduced imaging size of the patient relative to the first x-ray image;
determining whether the object of interest was successfully detected in the second x-ray image; and
in response to determining that the object of interest was not successfully detected in the second x-ray image:
generating an x-ray scatter image of a region beyond the area of interest determined in the first x-ray image.

16. The non-transitory computer readable medium of claim 15 , wherein detecting an object of interest in a first x-ray image comprises:
automatically detecting the object of interest in the first x-ray image using a probabilistic boosting tree (PBT) trained on annotated training data.

17. The non-transitory computer readable medium of claim 16 , wherein detecting an object of interest in a first x-ray image further comprises:
determining at least one low probability region of the first x-ray image based on information related to a guidance path of the object of interest; and
removing the determined at least one low probability region from a search space of the PBT prior to automatically detecting the object of interest in the first x-ray image using the PBT.

18. The non-transitory computer readable medium of claim 16 , wherein detecting an object of interest in a first x-ray image further comprises:
applying a steerable filter to the first x-ray image to identify at least one high contrast region of the first x-ray image; and
removing the identified at least one high contrast region from a search space of the PBT prior to automatically detecting the object of interest in the first x-ray image using the PBT.

19. The non-transitory computer readable medium of claim 15 , wherein determining an area of interest based on a predicted motion of the object of interest comprises:
predicting a next location of the object of interest by predicting a motion of the object of inte

Assignees

• Siemens Ag

Inventors

• Mountney Peter
• Maier Andreas
• Ionasec Razvan Ioan
• Boese Jan
• Comaniciu Dorin

Classifications

• A61B6/5211 Primary

  involving processing of medical diagnostic data · CPC title

• A61B6/06

  Diaphragms · CPC title

• A61B6/12

  Arrangements for detecting or locating foreign bodies · CPC title

• A61B6/545

  involving automatic set-up of acquisition parameters · CPC title

• G16H50/20

  for computer-aided diagnosis, e.g. based on medical expert systems · CPC title