Automatic generation of a vascular skeleton

• US 8,463,007 B2
• Filed: 05/17/2010
• Issued: 06/11/2013
• Est. Priority Date: 03/08/2007
• Status: Active Grant

• Current Assignee: Sync-Rx, Ltd. (Koninklijke Philips N.V.)
• Original Assignee: Sync-Rx, Ltd. (Koninklijke Philips N.V.)
• Inventors: Steinberg, Alexander, Philipp, Sagiv, Cohen, Ran, Tolkowsky, David
• Primary Examiner(s): BHATNAGAR, ANAND P
• Application Number:
  US12/781,294
• Publication Number:
  US 20100220917A1
• Time in Patent Office: 1,121 Days
• Field of Search: 382/100, 382/128, 382/129, 382/130, 382/121, 382/132, 382/167, 382/254, 382/256, 382/257, 382/258, 382/266, 382/267, 382/268, 382/269, 382/275, 128/922, 378 4- 27
• US Class Current: 382/128
• CPC Class Codes: A61B 17/12036 partial occlusion
• CPC Class Codes: A61B 17/1204 temporary occlusion
• CPC Class Codes: A61B 17/12136 Balloons
• CPC Class Codes: A61B 18/02 by cooling, e.g. cryogenic techniques devices for cooling specific reflex points of the body within cell-life limits A61H39/06
• CPC Class Codes: A61B 18/1492 having a flexible, catheter-like structure, e.g. for heart ablation A61B18/1477 takes precedence
• CPC Class Codes: A61B 18/24 with a catheter A61B18/26, A61B18/28 take precedence
• CPC Class Codes: A61B 2017/00252 for by-pass connections, i.e. connections from heart chamber to blood vessel or from blood vessel to blood vessel
• CPC Class Codes: A61B 2017/00694 with means correcting for movement of or for synchronisation with the body
• CPC Class Codes: A61B 2017/00703 correcting for movement of heart, e.g. ECG-triggered
• CPC Class Codes: A61B 2017/1205 Introduction devices
• CPC Class Codes: A61B 2017/22044 with a pointed tip
• CPC Class Codes: A61B 2017/22094 for crossing total occlusions, i.e. piercing
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/107 Visualisation of planned trajectories or target regions
• CPC Class Codes: A61B 2034/254 being adapted depending on the stage of the surgical procedure
• CPC Class Codes: A61B 2090/365 augmented reality, i.e. correlating a live optical image with another image
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 34/20 Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
• CPC Class Codes: A61B 34/25 User interfaces for surgical systems
• CPC Class Codes: A61B 5/0044 for the heart
• CPC Class Codes: A61B 5/7285 : for synchronising or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal A61B6/5205, A61B6/541, A61B8/5207, A61B8/543 take precedence
• CPC Class Codes: A61B 5/7289 : Retrospective gating, i.e. associating measured signals or images with a physiological event after the actual measurement or image acquisition, e.g. by simultaneously recording an additional physiological signal during the measurement or image acquisition
• CPC Class Codes: A61B 6/12 : Arrangements for detecting or locating foreign bodies
• CPC Class Codes: A61B 6/469 : for selecting a region of interest [ROI]
• CPC Class Codes: A61B 6/481 : involving the use of contrast agents
• CPC Class Codes: A61B 6/501 : for diagnosis of the head, e.g. neuroimaging or craniography
• CPC Class Codes: A61B 6/503 : for diagnosis of the heart
• CPC Class Codes: A61B 6/504 : for diagnosis of blood vessels, e.g. by angiography
• CPC Class Codes: A61B 6/5217 : extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: A61B 6/5247 : combining images from an ionising-radiation diagnostic technique and a non-ionising radiation diagnostic technique, e.g. X-ray and ultrasound
• CPC Class Codes: A61B 6/541 : involving acquisition triggered by a physiological signal
• CPC Class Codes: A61B 8/0883 : for diagnosis of the heart
• CPC Class Codes: A61B 8/0891 : for diagnosis of blood vessels
• CPC Class Codes: A61B 8/543 : involving acquisition triggered by a physiological signal
• CPC Class Codes: A61F 2/958 : Inflatable balloons for placing stents or stent-grafts
• CPC Class Codes: G06T 11/60 : Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 2207/10121 : Fluoroscopy
• CPC Class Codes: G06T 2207/30048 : Heart; Cardiac
• CPC Class Codes: G06T 2207/30101 : Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 5/00 : Image enhancement or restoration
• CPC Class Codes: G06T 7/0012 : Biomedical image inspection
• CPC Class Codes: G06T 7/0014 : using an image reference approach
• CPC Class Codes: G06T 7/13 : Edge detection
• CPC Class Codes: G06T 7/246 : using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/62 : of area, perimeter, diameter or volume
• CPC Class Codes: G06V 2201/034 : of medical instruments
• CPC Class Codes: G06V 40/103 : Static body considered as a whole, e.g. static pedestrian or occupant recognition
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment

Abstract

Apparatus and methods are described for receiving into at least one processor at least one image of blood vessels of a subject. Using image processing, discontinuous lines that correspond to paths of at least a portion of the blood vessels in the image are automatically derived, the lines having end points at discontinuities in the lines. Continuous lines that correspond to the paths of the portion of the blood vessels in the image are automatically generated by bridging the discontinuities in the discontinuous lines. An output is generated by the processor, based on the continuous lines. Other embodiments are also described.

Claims

1. A method, comprising:

receiving into at least one processor at least one image of blood vessels of a subject;

using image processing, automatically deriving discontinuous lines that correspond to paths of at least a portion of the blood vessels in the image, the lines having end points at discontinuities in the lines;

automatically generating continuous lines that correspond to the paths of the portion of the blood vessels in the image by bridging the discontinuities in the discontinuous lines; and

generating an output by the processor, based on the continuous lines,

wherein bridging the discontinuities comprises using a technique selected from the group consisting of;

bridging the discontinuities based upon a shortest-path algorithm, and

bridging the discontinuities based upon a known structure of the portion of the blood vessels.

2. The method according to claim 1, wherein receiving the at least one image comprises receiving into the processor a plurality of images of the blood vessels, and wherein generating the output comprises overlaying the lines on an image stream that is based upon the plurality of images.

3. The method according to claim 1, wherein generating the output comprises overlaying the lines on the image of the blood vessels.

4. The method according to claim 1, wherein generating the output comprises overlaying the lines on a current real time image stream of the blood vessels.

5. The method according to claim 1, wherein generating the lines comprises generating lines corresponding to the paths of the blood vessels during a given phase of a motion cycle of the blood vessels, and wherein generating the output comprises overlaying the lines on an image stream of the blood vessels that is gated to the given phase.

6. The method according to claim 1, wherein generating the continuous lines comprises generating the continuous lines in real time.

7. The method according to claim 1, wherein generating the continuous lines comprises generating the continuous lines in near real time.

8. The method according to claim 1, further comprising automatically determining a location of edge lines of the portion of the blood vessels, based upon the lines that correspond to the paths.

9. The method according to claim 1, wherein deriving the discontinuous lines comprises deriving discontinuous lines that correspond to center lines of the portion of the blood vessels.

10. The method according to claim 1, wherein deriving the discontinuous lines comprises deriving lines corresponding to paths of the blood vessels, based upon the lines having greater visibility than other lines corresponding to paths of the blood vessels in the at least one image.

11. The method according to claim 1, wherein adjacent to at least one first end point of the end points, there are a plurality of second end points of the end points, and wherein bridging the discontinuities comprises determining to which of the second end points to bridge from the first end point.

12. The method according to claim 1, wherein receiving the image comprises receiving an image that was acquired in a presence of a contrast agent.

13. The method according to claim 1, wherein bridging the discontinuities comprises bridging the discontinuities based upon a shortest-path algorithm.

14. The method according to claim 1, wherein bridging the discontinuities comprises bridging the discontinuities based upon a known structure of the portion of the blood vessels.

15. Apparatus for use with:

an image-acquisition device configured to acquire at least one image of blood vessels of a subject; and

a display, the apparatus comprising;

at least one processor, comprising;

image-receiving functionality configured to receive the at least one image into the processor;

line-derivation functionality configured, using image processing, to automatically derive discontinuous lines that correspond to paths of at least a portion of the blood vessels in the image, the lines having end points at discontinuities in the lines;

line-bridging functionality configured to, automatically, generate continuous lines that correspond to the paths of the portion of the blood vessels in the image, by bridging the discontinuities in the discontinuous lines, the line-bridging functionality being configured to bridge the discontinuities based upon a technique selected from the group consisting of;

bridging the discontinuities based upon a shortest-path algorithm, and

bridging the discontinuities based upon a known structure of the portion of the blood vessels; and

display-driving functionality configured to drive the display to display an output to a user based on the continuous lines.

16. The apparatus according to claim 15, wherein the processor further comprises edge-line-determination functionality configured to determine a location of edge lines of the portion of the blood vessels, based upon the lines that correspond to the paths.

17. The apparatus according to claim 15, wherein the line-derivation functionality is configured to derive discontinuous lines that correspond to center lines of the portion of the blood vessels.

18. The apparatus according to claim 15, wherein the line-derivation functionality is configured to derive lines corresponding to paths of the blood vessels, based upon the lines having greater visibility than other lines corresponding to paths of the blood vessels in the at least one image.

19. The apparatus according to claim 15, wherein adjacent to at least one first end point of the end points, there are a plurality of second end points of the end points, and wherein the line-bridging functionality is configured to determine to which of the second end points to bridge from the first end point.

20. The apparatus according to claim 15, wherein the line-bridging functionality is configured to bridge the discontinuities based upon a shortest-path algorithm.

21. The apparatus according to claim 15, wherein the line-bridging functionality is configured to bridge the discontinuities based upon a known structure of the portion of the blood vessels.