Vascular data processing and image registration systems, methods, and apparatuses

• US 9,907,527 B2
• Filed: 03/02/2016
• Issued: 03/06/2018
• Est. Priority Date: 03/12/2013
• Status: Active Grant

• Current Assignee: LightLab Imaging, Inc. (Abbott Laboratories)
• Original Assignee: LightLab Imaging, Inc. (Abbott Laboratories)
• Inventors: Dascal, Lorina, Winkler, Itai, Cohen, Stavit, Cohen, Amit, Adler, Desmond C.
• Primary Examiner(s): STREGE, JOHN B
• Application Number:
  US15/058,338
• Publication Number:
  US 20160174925A1
• Time in Patent Office: 734 Days
• CPC Class Codes: A61B 2090/364 Correlation of different images or relation of image positions in respect to the body
• CPC Class Codes: A61B 2090/3735 Optical coherence tomography [OCT]
• CPC Class Codes: A61B 2090/3966 Radiopaque markers visible in an X-ray image
• CPC Class Codes: A61B 5/0035 adapted for acquisition of images from more than one imaging mode, e.g. combining MRI and optical tomography
• CPC Class Codes: A61B 5/0066 Optical coherence imaging
• CPC Class Codes: A61B 5/0073 by tomography, i.e. reconstruction of 3D images from 2D projections A61B5/0066 takes precedence
• CPC Class Codes: A61B 5/0084 for introduction into the body, e.g. by catheters A61B5/1459 takes precedence
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/12 Arrangements for detecting or locating foreign bodies
• CPC Class Codes: A61B 6/4417 related to combined acquisition of different diagnostic modalities
• CPC Class Codes: A61B 6/463 characterised by displaying multiple images or images and diagnostic data on one display
• CPC Class Codes: A61B 6/481 involving the use of contrast agents
• CPC Class Codes: A61B 6/487 involving fluoroscopy
• CPC Class Codes: A61B 6/504 for diagnosis of blood vessels, e.g. by angiography
• CPC Class Codes: A61B 6/507 for determination of haemodynamic parameters, e.g. perfusion CT
• 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 6/5258 involving detection or reduction of artifacts or noise
• CPC Class Codes: A61B 8/12 in body cavities or body tracts, e.g. by using catheters catheters per se A61M25/00
• CPC Class Codes: A61B 8/4245 involving determining the position of the probe, e.g. with respect to an external reference frame or to the patient
• CPC Class Codes: A61B 8/565 : involving data transmission via a network
• CPC Class Codes: A61M 2025/105 : having a balloon suitable for drug delivery, e.g. by using holes for delivery, drug coating or membranes
• CPC Class Codes: A61M 25/104 : used for angioplasty
• CPC Class Codes: G06T 2207/10101 : Optical tomography; Optical coherence tomography [OCT]
• CPC Class Codes: G06T 2207/30101 : Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 2207/30204 : Marker
• CPC Class Codes: G06T 7/0012 : Biomedical image inspection
• CPC Class Codes: G06T 7/11 : Region-based segmentation

Abstract

In part, the invention relates to processing, tracking and registering angiography images and elements in such images relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT). Registration between such imaging modalities is facilitated by tracking of a marker of the intravascular imaging probe performed on the angiography images obtained during a pullback. Further, detecting and tracking vessel centerlines is used to perform a continuous registration between OCT and angiography images in one embodiment.

Claims

1. A method of detecting an intravascular probe marker comprising:

obtaining a first frame of angiography image data that is substantially free of contrast agent image data and includes the intravascular probe marker, the first frame stored in one or more electronic memory devices;

obtaining a second frame of angiography image data that comprises contrast agent image data in a vicinity of the intravascular probe marker, the second frame stored in the one or more electronic memory devices;

detecting, using an intravascular data collection system, the intravascular probe marker in the first frame and the second frame;

processing the plurality of pullback frames using a Hessian-based vessleness filter; and

tracking the intravascular probe marker from one of the first frame or the second frame through the plurality of pullback frames using template matching.

2. The method of claim 1, further comprising:

applying an image processing transform, using an intravascular data collection system, to the second frame to remove or modify a feature in the second frame; and

increasing an intensity of a plurality of pixels in the second frame, the plurality of pixels comprising a guidewire image in the second frame.

3. The method of claim 1 further comprising:

generating an average intensity value for a plurality of images; and

subtracting the average intensity from the first or second frame.

4. The method of claim 1 further comprising:

applying a bottom hat operator, using an intravascular data collection system, to the second frame; and

applying, using an intravascular data collection system, a morphological close operation.

8. The method of claim 1 further comprising:

removing a shadow from the first frame and the second frame;

increasing a contrast level of a guidewire on one of the first frame or second frame; and

performing a morphological image reconstruction for each marker candidate.

5. A method of detecting an intravascular probe marker comprising:

obtaining a first frame of angiography image data that is substantially free of contrast agent image data and includes the intravascular probe marker, the first frame stored in one or more electronic memory devices;

obtaining a second frame of angiography image data that comprises contrast agent image data in a vicinity of the intravascular probe marker, the second frame stored in the one or more electronic memory devices; and

detecting, using an intravascular data collection system, the intravascular probe marker in the first frame and the second frame,

wherein detecting the intravascular probe marker comprises;

filtering candidate markers comprising pixels in the first frame and the second frame by applying a multiscale Laplacian of Gaussian operator on the first frame and the second frame; and

performing a non-maxima suppression process to identify blobs having a relative maximum in a neighborhood of pixels.

6. A method of detecting an intravascular probe marker comprising:

obtaining a first frame of angiography image data that is substantially free of contrast agent image data and includes the intravascular probe marker, the first frame stored in one or more electronic memory devices;

obtaining a second frame of angiography image data that comprises contrast agent image data in a vicinity of the intravascular probe marker, the second frame stored in the one or more electronic memory devices;

detecting, using an intravascular data collection system, the intravascular probe marker in the first frame and the second frame;

generating a guidewire-based potential by applying a Euclidian distance transform on a binary image; and

applying an exponent to a negative fractional power times the distance transform.

7. The method of claim 6 further comprising determining a plurality of geodesic distances based on the guidewire-based potential using a fast marching method.

9. A method of detecting an intravascular probe marker comprising:

obtaining a first frame of angiography image data that is substantially free of contrast agent image data and includes the intravascular probe marker, the first frame stored in one or more electronic memory devices;

obtaining a second frame of angiography image data that comprises contrast agent image data in a vicinity of the intravascular probe marker, the second frame stored in the one or more electronic memory devices;

detecting, using an intravascular data collection system, the intravascular probe marker in the first frame and the second frame; and

tracking the intravascular probe marker through a plurality of frames obtained during a pullback using a Viterbi dynamic programming method.