# US 2013/0278776 A1 · Automatic left ventricular function evaluation

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2013/0278776 A1
- Document ID: US20130278776A1
- Status: Published application
- Kind: A1
- Application number: 13/977,877
- Filed: 2011-12-29
- Published: 2013-10-24
- Earliest claimed: 2010-12-29
- Assignees: Diacardio Ltd.
- Inventors: Hugo Guterman; Noah Liel; Marina Yaacobi
- Web page: https://patentgrep.com/patent/US20130278776A1

## CPC

- G06T 7/0012: {Biomedical image inspection}
- A61B 8/065: {to determine blood output from the heart}
- A61B 8/0883: {for diagnosis of the heart}
- A61B 8/5223: {for extracting a diagnostic or physiological parameter from medical diagnostic data (for algorithms to analyse biomedical images G06T7/0012)}
- G06T 7/0016: {involving temporal comparison}
- G06T 7/12: Edge-based segmentation
- G06T 7/136: involving thresholding
- G06T 7/174: involving the use of two or more images
- G06T 7/181: involving edge growing; involving edge linking
- G16H 50/30: for calculating health indices; for individual health risk assessment
- A61B 8/543: {involving acquisition triggered by a physiological signal}
- G06T 2207/10016: Video; Image sequence
- G06T 2207/10132: Ultrasound image
- G06T 2207/20032: Median filtering
- G06T 2207/30048: Heart; Cardiac
- 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

A method for automatic left ventricular (LV) inner border detection, the method comprising: performing image mapping on an echocardiogram, to produce a multi-level image map; converting the image map into a binary image, by attributing pixels of one or more darker levels of the image map to the LV cavity and pixels of one or more lighter levels of the image map to the myocardium; applying a radial filter to contours of the myocardium in the binary image, to extract an approximate inner border of the LV; and performing shape modeling on the approximate inner border, to determine the LV inner border.

## Claims

### Claim 1

A method for automatic left ventricular (LV) inner border detection, the method comprising:
performing image mapping on an echocardiogram, to produce a multi-level image map;
converting the image map into a binary image, by attributing pixels of one or more darker levels of the image map to the LV cavity and pixels of one or more lighter levels of the image map to the myocardium;
applying a radial filter to contours of the myocardium in the binary image, to extract an approximate inner border of the LV; and
performing shape modeling on the approximate inner border, to determine the LV inner border.

### Claim 2 (depends on 1)

The method according to claim 1, wherein the multi-level image map comprises a 3-level image map, and wherein the one or more darker levels of the image map comprise two darker levels and the one or more lighter levels of the image map comprise one lighter level.

### Claim 3 (depends on 1)

The method according to claim 1, further comprising, prior to performing the image mapping, automatically detecting a region of interest in the echocardiogram, wherein the region of interest encloses the LV.

### Claim 4 (depends on 3)

The method according to claim 3, wherein the automatic detection of the region of interest comprises:
producing an inverted binary version of the echocardiogram;
computing a column histogram of white pixels in the inverted binary version; and
defining an area delimited between two minimum points of the column histogram as the region of interest.

### Claim 5 (depends on 1)

The method according to claim 1, wherein the image mapping comprises segmenting the echocardiogram using piece-wise histogram equalization.

### Claim 6 (depends on 5)

The method according to claim 5, wherein the piece-wise histogram equalization comprises determining a central axis of the LV and dividing the LV appearing in the echocardiogram, based on entropy levels in the histogram, into a plurality of rectangular segments situated on lateral and septal sides of the central axis.

### Claim 7 (depends on 1)

The method according to claim 1, wherein the echocardiogram comprises an apical view echocardiogram.

### Claim 8 (depends on 7)

The method according to claim 7, wherein the apical view comprises a four-chamber apical view.

### Claim 9 (depends on 8)

The method according to claim 8, wherein the multi-level image map comprises a 3-level image map, and wherein the one or more darker levels of the image map comprise two darker levels and the one or more lighter levels of the image map comprise one lighter level.

### Claim 10 (depends on 7)

The method according to claim 7, wherein the apical view comprises a two-chamber apical view.

### Claim 11 (depends on 10)

The method according to claim 10, wherein the multi-level image map comprises a 3 to 5-level image map.

### Claim at position 12

12-31. (canceled)

### Claim 32

An ultrasonic imaging device, comprising:
an ultrasonic probe configured to acquire an echocardiogram; and
a processing unit connected to said probe and configured to automatically closely approximate an inner border of the left ventricular (LV) appearing in the echocardiogram, the approximation being based on shape modeling of a pre-processed echocardiogram of the LV.

### Claim 33 (depends on 32)

The ultrasonic imaging device according to claim 32, wherein said processing unit is further configured to:
perform image mapping on the echocardiogram, to produce a multi-level image map;
convert the multi-level image map to a binary image, by attributing pixels of one or more darker levels of the image map to the LV cavity and pixels of one or more lighter levels of the image map to the myocardium; and
apply a radial filter to contours of the myocardium in the binary image, to extract an approximate inner border of the LV.

### Claim 34 (depends on 33)

The ultrasonic imaging device according to claim 33, wherein the multi-level image map comprises a 3-level image map, and wherein the one or more darker levels of the image map comprise two darker levels and the one or more lighter levels of the image map comprise one lighter level.

### Claim 35 (depends on 33)

The ultrasonic imaging device according to claim 33, wherein the image mapping comprises segmenting the echocardiogram using piece-wise histogram equalization.

### Claim 36 (depends on 33)

The ultrasonic imaging device according to claim 33, wherein said processing unit is further configured to, prior to performing the image mapping, automatically detect a region of interest in the echocardiogram, wherein the region of interest encloses the LV.

### Claim 37 (depends on 36)

The ultrasonic imaging device according to claim 36, wherein the automatic detection of the region of interest comprises:
producing an inverted binary version of the echocardiogram;
computing a column historgram of white pixels in the inverted binary version; and
defining an area delimited between two minimum points of the column historgram as the region of interest.

### Claim 38 (depends on 33)

The ultrasonic imaging device according to claim 33, wherein the echocardiogram comprises an apical view echocardiogram.

### Claim 39 (depends on 38)

The ultrasonic imaging device according to claim 38, wherein the apical view comprises a four-chamber apical view.

### Claim 40 (depends on 39)

The ultrasonic imaging device according to claim 39, wherein the multi-level image map comprises a 3-level image map, and wherein the one or more darker levels of the image map comprise two darker levels and the one or more lighter levels of the image map comprise one lighter level.

### Claim at position 22

41-65. (canceled)