# US 8,542,895 B2 · Methods and systems for color flow dynamic frame persistence

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- Number: US 8,542,895 B2
- Document ID: US8542895B2
- Status: Granted
- Kind: B2
- Application number: 12/960,190
- Filed: 2010-12-03
- Published: 2011-07-07
- Granted: 2013-09-24
- Earliest claimed: 2010-01-05
- Assignees: Shenzhen Mindray Bio-Medical Electronics Co., Ltd.
- Applicants: Yaoxian Zou; Bin Yao; Qinjun Hu
- Inventors: Yaoxian Zou; Bin Yao; Qinjun Hu
- Web page: https://patentgrep.com/patent/US8542895B2

## CPC

- G06T 7/0012: {Biomedical image inspection}
- A61B 8/06: Measuring blood flow
- A61B 8/5215: {involving processing of medical diagnostic data}
- A61B 8/5223: {for extracting a diagnostic or physiological parameter from medical diagnostic data (for algorithms to analyse biomedical images G06T7/0012)}
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

Methods and systems for color flow dynamic frame persistence in ultrasonic imaging are provided.

## Claims

### Claim 1

An image processing method for calculating blood vessel direction of a flow velocity image comprising a plurality of point-regions, each point-region associated with a central point, the method comprising:
distinguishing each of the point-regions in the flow velocity image as point-regions in a flow region and point-regions in a background region;
estimating a rough direction of a computing point-region by:
setting a plurality of directions and respectively calculating the number of point-regions in the flow region connecting with the computing point-region in each direction; and
taking the direction with the maximum number of point-regions as the rough direction of the computing point-region;
determining middle point-regions on the direction perpendicular to the rough direction in a neighborhood;
determining a line connecting the central points of the middle point-regions as a median line of the blood vessel in the neighborhood, wherein the neighborhood is centered on the computing point-region and includes a plurality of point-regions in the flow region in the rough direction; and
calculating the direction of the blood vessel on the computing point-region according to the determined median line of the blood vessel,
wherein calculating comprises applying a linear fitting or Hough Transform to the determined median line of the blood vessel.

### Claim 2 (depends on 1)

The method of claim 1, wherein distinguishing comprises binarizing the image by marking the point-regions whose values are smaller than a predefined threshold as zero and the remaining point-regions as one, thereby distinguishing the point-regions in the flow region and the point-regions in the background region.

### Claim 3 (depends on 1)

The method of claim 1 wherein the plurality of directions is selected from the group consisting of two directions, or four directions, and eight directions.

### Claim 4 (depends on 3)

The method of claim 3, wherein the plurality of directions is selected from the group consisting of a set of directions comprising horizontal and vertical directions, and a set of directions comprising 0°, 45°, 90° and 135°.

### Claim 5

A system for calculating blood vessel direction of a flow velocity image comprising a plurality of point-regions, each point-region associated with a central point, the system comprising:
a processor;
a distinguishing module configured to distinguish each of the point-regions in the blood flow velocity image as point-regions in a flow region and point-regions in a background region;
an estimation module configured to set a plurality of directions and respectively calculate the number of the point-regions in the flow region connecting with a computing point-region each direction, and take the direction with the maximum number as the rough direction of the computing point-region;
a determination module configured to determine middle point-regions on the direction perpendicular to the rough direction in a neighborhood;
determining a line connecting the central points of the middle point-regions as a median line of the blood vessel in the neighborhood, wherein the neighborhood takes the computing point-region as a center point-regions and comprises a plurality of point-regions in the flow region in the rough direction; and
a computation module configured to calculate the direction of the blood vessel on the computing point-region according to the determined median line of the blood vessel,
wherein the computation module is configured to applying a linear fitting or Hough Transform to the determined median line of the blood vessel.

### Claim 6 (depends on 5)

The system of claim 5, wherein the first distinguishing module is configured to binarize the image by marking the point-regions whose values are smaller than a predefined threshold as zero and the remaining point-regions as 1, thereby distinguishing the point-regions in the flow region and the point-regions in the background region.

### Claim 7 (depends on 5)

The system of claim 5, wherein the plurality of directions comprises two directions, or four directions, or eight directions.

### Claim 8

A non-transitory computer-readable medium comprising program code that causes a processor to perform operations for calculating blood vessel direction of a flow velocity image comprising a plurality of point-regions, each point-region associated with a central point, the operations comprising:
distinguishing each of the point-regions in the flow velocity image as point-regions in a flow region and point-regions in a background region;
estimating a rough direction of a computing point-region by setting a plurality of directions and respectively calculating the number of point-regions in the flow region connecting with the computing point-region in each direction, and taking the direction with the maximum number of point-regions as the rough direction of the computing point-region;
determining middle point-regions on the direction perpendicular to the rough direction in a neighborhood;
determining a line connecting the central points of the middle point-regions as a median line of the blood vessel in the neighborhood, wherein the neighborhood is centered around the computing point-region and includes a plurality of point-regions in the flow region in the rough direction; and
calculating the direction of the blood vessel on the computing point-region according to the determined median line of the blood vessel,
wherein calculating comprises applying a linear fitting or Hough Transform to the determined median line of the blood vessel.