# US 9,814,433 B2 · Creating a vascular tree model

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- Number: US 9,814,433 B2
- Document ID: US9814433B2
- Status: Granted
- Kind: B2
- Application number: 14/761,079
- Filed: 2014-01-15
- Published: 2015-11-26
- Granted: 2017-11-14
- Earliest claimed: 2012-10-24
- Assignees: CathWorks Ltd.
- Applicants: CathWorks Ltd.
- Inventors: Nessi Benishti; Ifat Lavi; Ran Kornowski; Idit Avrahami; Guy Lavi
- Web page: https://patentgrep.com/patent/US9814433B2

## CPC

- A61B 6/466: {adapted to display 3D data}
- A61B 5/02007: {Evaluating blood vessel condition, e.g. elasticity, compliance}
- A61B 5/026: Measuring blood flow {(A61B3/1233, A61B3/1241 take precedence)}
- A61B 6/022: {Stereoscopic imaging}
- A61B 6/503: {for diagnosis of the heart}
- A61B 6/504: {for diagnosis of blood vessels, e.g. by angiography}
- A61M 5/007: {for contrast media}
- G06T 7/0012: {Biomedical image inspection}
- G06T 7/55: from multiple images
- G06T 12/30: Image post-processing, e.g. metal artefact correction
- G16H 30/20: for handling medical images, e.g. DICOM, HL7 or PACS
- G16H 50/30: for calculating health indices; for individual health risk assessment
- G16H 50/50: for simulation or modelling of medical disorders
- A61B 5/021: Measuring pressure in heart or blood vessels
- A61B 5/0263: {using NMR}
- A61B 5/7285: {for synchronizing or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal}
- A61B 6/02: Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B 6/032: {Transmission computed tomography [CT]}
- A61B 6/037: {Emission tomography}
- A61B 6/481: {involving the use of contrast agents}
- A61B 6/507: {for determination of haemodynamic parameters, e.g. perfusion CT}
- A61B 6/5217: {extracting a diagnostic or physiological parameter from medical diagnostic data}
- A61B 6/5258: {involving detection or reduction of artifacts or noise}
- A61B 6/541: {involving acquisition triggered by a physiological signal}
- A61B 8/06: Measuring blood flow
- A61B 2576/023: for the heart
- G06T 2200/04: involving 3D image data
- G06T 2207/10072: Tomographic images
- G06T 2207/10116: X-ray image
- G06T 2207/20044: Skeletonization; Medial axis transform
- G06T 2207/20072: Graph-based image processing
- G06T 2207/30101: Blood vessel; Artery; Vein; Vascular
- G06T 2207/30104: Vascular flow; Blood flow; Perfusion
- G06T 2207/30172: Centreline of tubular or elongated structure
- G06T 2210/41: Medical
- G06T 2211/404: Angiography
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- A61M: DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY (introducing media into or onto the bodies of animals A61D7/00; means for inserting tampons A61F13/26; devices for administering food or medicines orally A61J; containers for collecting, storing or administering blood or medical fluids A61J1/05); DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY (surgery A61B; chemical aspects of surgical articles A61L); DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR {(Electrotherapy, e.g. producing anaesthesia by the use of alternating or intermittent currents A61N1/36021)}
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

A method for vascular modeling is disclosed. The method, in some embodiments, comprises receiving a plurality of 2-D angiographic images of a portion of a vasculature of a subject, and processing the images to automatically detect 2-D features, for example, paths along vascular extents, which are projected into 3-D to determine homologous features among blood vessels. In some embodiments, projection and/or image registration is iteratively altered to improve feature position matching. Based on 3-D vascular extents and their registration to 2-D images, additional features such as vascular width are optionally determined and added to the model.

## Claims

### Claim 1

A method for construction of a vascular tree model comprising:
receiving by image processing circuitry a plurality of 2-D angiographic images showing blood vessel segments of a portion of a vasculature of a subject;
extracting automatically by the image processing circuitry, from each of said plurality of 2-D angiographic images, an image feature set comprising 2-D feature positions of said blood vessel segments; and
identifying homologous vascular branches among the 2-D angiographic images using said blood vessel segments, wherein the identifying comprises:
adjusting automatically by the image processing circuitry said 2-D feature positions to reduce relative position error in a common 3-D coordinate system to which each said image feature set is back-projectable, and
then associating automatically by the image processing circuitry image features of the image feature sets as representing homologous vascular branches, based on their projection from the planes of the 2-D angiographic images to common blood vessel segment regions in said common 3-D coordinate system.

### Claim 2 (depends on 1)

The method of claim 1, wherein the image feature set which is extracted comprises a centerline data set including 2-D centerline positions ordered along said blood vessel segments.

### Claim 3 (depends on 2)

The method of claim 2, wherein said adjusting and associating are performed with elements of said centerline data set.

### Claim 4 (depends on 2)

The method of claim 2, wherein said adjusting comprises registration of said 2-D images in 3-D space according to parameters which bring said 2-D centerline positions into closer correspondence among their 3-D back-projections.

### Claim 5 (depends on 2)

The method of claim 2, comprising estimating a metric of radial vascular width based on values of at least one of said plurality of 2-D angiographic images along lines perpendicular to said ordered 2-D centerline positions.

### Claim 6 (depends on 2)

The method of claim 2, wherein said adjusting comprises adjusting of said 2-D feature positions based on projection of said common 3-D coordinate system into the 2-D plane of at least one of said plurality of 2-D angiographic images.

### Claim 7 (depends on 1)

The method of claim 1, wherein information required for said associating automatically of image features is entirely provided before review of said images by a human operator.

### Claim 8 (depends on 1)

The method of claim 1, further comprising defining a surface corresponding to a shape of the heart of the subject, and using said surface as a constraint for said associating of said image features.

### Claim 9 (depends on 1)

The method of claim 1, wherein said images are acquired upon injection of a contrast agent to said vasculature, and further comprising:
determining temporal characteristics of the movement of said contrast agent through said vasculature; and
constraining said 2-D feature positions based on said temporal characteristics.

### Claim 10 (depends on 1)

The method of claim 1, wherein said portion of said vasculature comprises coronary arteries.

### Claim 11 (depends on 1)

The method of claim 1, further comprising:
inspecting projections from the blood vessel segment regions associated with the image features to the planes of 2-D angiographic images to identify image portions representing blood vessel segment regions for which a physical characteristic is to be calculated;
selecting automatically by image processing circuitry a portion of at least one of said plurality of 2-D angiographic images, the portion comprising a representation of said associated image features identified by the inspecting; and
calculating a physical characteristic of at least one of the blood vessel segments, based on the selected image portion.

### Claim 12 (depends on 1)

A computer software product, comprising a computer-readable storage medium in which program instructions are stored, which instructions, when read by a computer, cause the computer to receive a plurality of 2-D angiographic images of a portion of a vasculature and execute the method according to claim 1.

### Claim 13

A method for construction of a vascular tree model comprising:
receiving by image processing circuitry a plurality of 2-D angiographic images showing blood vessel segments of a portion of a vasculature of a subject;
extracting automatically by the image processing circuitry, from each of said plurality of 2-D angiographic images, an image feature set comprising 2-D feature positions of said blood vessel segments;
adjusting automatically by the image processing circuitry said 2-D feature positions to reduce relative position error in a common 3-D coordinate system to which each said image feature set is back-projectable;
wherein the adjusting comprises iteratively determining a consensus centerline in the common 3-D coordinate system for the feature sets from the plurality of 2-D angiographic images, and wherein the relative position error is calculated based on differences in positions of the projection of the consensus centerline to coordinate systems of the plurality of 2-D angiographic images from positions of the respective image feature sets of the plurality of 2-D angiographic images; and
associating automatically by the image processing circuitry image features of the image feature sets to one another based on their projection from the planes of the 2-D angiographic images to common blood vessel segment regions in said common 3-D coordinate system.

### Claim 14 (depends on 13)

The method of claim 13, wherein the image feature set comprises a centerline data set including 2-D centerline positions ordered along said blood vessel segments.

### Claim 15 (depends on 14)

The method of claim 14, wherein said adjusting and associating are performed with elements of said centerline data set.

### Claim 16 (depends on 14)

The method of claim 14, wherein said adjusting comprises registration of said 2-D images in 3-D space according to parameters which bring said 2-D centerline positions into closer correspondence among their 3-D back-projections.

### Claim 17 (depends on 14)

The method of claim 14, comprising estimating a metric of radial vascular width based on values of at least one of said plurality of 2-D angiographic images along lines perpendicular to said ordered 2-D centerline positions.

### Claim 18 (depends on 14)

The method of claim 14, wherein said adjusting comprises adjusting of said 2-D feature positions based on projection of said common 3-D coordinate system into the 2-D plane of at least one of said plurality of 2-D angiographic images.

### Claim 19 (depends on 13)

The method of claim 13, wherein information for said associating automatically of image features is provided before review of said 2-D angiographic images by a human operator.

### Claim 20 (depends on 13)

The method of claim 13, further comprising defining a surface corresponding to a shape of the heart of the subject, and using said surface as a constraint for said associating of said image features.

### Claim 21 (depends on 13)

The method of claim 13, wherein said images are acquired upon injection of a contrast agent to said vasculature, and further comprising:
determining temporal characteristics of the movement of said contrast agent through said vasculature; and
constraining said 2-D feature positions based on said temporal characteristics.

### Claim 22 (depends on 13)

The method of claim 13, wherein said portion of said vasculature comprises coronary arteries.

### Claim 23 (depends on 13)

The method of claim 13, further comprising:
inspecting projections from the blood vessel segment regions associated with the image features to the planes of 2-D angiographic images to identify image portions representing blood vessel segment regions for which a physical characteristic is to be calculated;
selecting automatically by image processing circuitry a portion of at least one of said plurality of 2-D angiographic images, the portion comprising a representation of said associated image features identified by the inspecting; and
calculating a physical characteristic of at least one of the blood vessel segments, based on the selected image portion.