METHOD AND SYSTEM FOR MEASURING A VOLUME OF AN ORGAN OF INTEREST

• US 20180085043A1
• Filed: 09/13/2017
• Published: 03/29/2018
• Est. Priority Date: 09/26/2016
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Panicker, Mahesh R., Frigstad, Sigmund, Annangi, Pavan Kumar V, Varna, Srinivas, Patil, Abhijit Vishwas, Torp, Anders Herman
• Granted Patent: US 10,806,391 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 5/1073 Measuring volume, e.g. of limbs
• CPC Class Codes: A61B 5/1075 for measuring dimensions by non-invasive methods, e.g. for determining thickness of tissue layer A61B8/0858 takes precedence
• CPC Class Codes: A61B 5/204 Determining bladder volume
• CPC Class Codes: A61B 5/4238 stomach
• CPC Class Codes: A61B 8/085 for locating body or organic structures, e.g. tumours, calculi, blood vessels, nodules
• CPC Class Codes: A61B 8/0858 involving measuring tissue layers, e.g. skin, interfaces
• CPC Class Codes: A61B 8/4254 using sensors mounted on the probe
• CPC Class Codes: A61B 8/4427 Device being portable or laptop-like
• CPC Class Codes: A61B 8/4472 Wireless probes
• CPC Class Codes: A61B 8/466 adapted to display 3D data 3D imaging and stereoscopic displays in devices for short-range imaging with acoustic waves G01S15/8993 and G01S7/52068, respectively; 3D image rendering G06T15/00; manipulating 3D models for computer graphics G06T19/00
• CPC Class Codes: A61B 8/48 Diagnostic techniques A61B8/13 takes precedence
• CPC Class Codes: A61B 8/485 involving measuring strain or elastic properties
• CPC Class Codes: A61B 8/486 involving arbitrary m-mode
• CPC Class Codes: A61B 8/488 involving Doppler signals
• CPC Class Codes: A61B 8/5207 involving processing of raw data to produce diagnostic data, e.g. for generating an image reconstruction G06T11/00
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 2207/30056 Liver; Hepatic
• CPC Class Codes: G06T 2207/30084 Kidney; Renal
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/50 : Depth or shape recovery
• CPC Class Codes: G06T 7/62 : of area, perimeter, diameter or volume

Abstract

In an embodiment of the subject matter described herein a system is provided. The system includes a portable host system having one or more processors and a memory for storing a plurality of applications. The one or more processors configured to execute programmed instructions of a select application by performing one or more operations, which include obtain a set of frames of 2D ultrasound images, develop a prospect model indicating a likelihood that frames within the set include an organ of interest (OOI), identify primary and secondary reference frames from the set of the frames based on the prospect model, determine a characteristic of interest in the primary reference frame, select a candidate shape for the OOI based on the character of interest in the primary reference frame, and adjust the candidate shape based on the secondary reference frames to form a resultant shape for the OOI.

Claims

1. A method comprising:

obtaining a set of frames of 2D ultrasound images;

using one or more processors to;

develop a prospect model indicating a likelihood that frames within the set include an organ of interest (OOI);

identify primary and secondary reference frames from the set of the frames based on the prospect model;

determine a characteristic of interest in the primary reference frame;

select a candidate shape for the OOI based on the character of interest in the primary reference frame; and

adjust the candidate shape based on the secondary reference frames to form a resultant shape for the OOI.

2. The method of claim 1, wherein the identify operation includes identifying, from the set of frames, an ultrasound image that intersects a center of the OOI, the ultrasound image representing the primary reference frame.

3. The method of claim 1, wherein the identify operation includes identifying, from the set of frames, ultrasound images intersects intermediate and peripheral edges of the OOI, the ultrasound images representing the primary and secondary reference frames.

4. The method of claim 1, wherein the develop operation includes identifying a pixel pattern between adjacent frames in the set of frames and deriving the prospect model based on the pixel pattern.

5. The method of claim 1, wherein the develop operation includes identifying regions of interest in adjacent frames in the set of frames, calculating pixel intensity information for the regions of interest, and deriving the prospect model based on the pixel intensity information.

6. The method of claim 1, wherein the develop operation includes determining tilt angle information regarding for at least a portion of the set of frames, and deriving the prospect model based on the tilt angle information.

7. The method of claim 1, wherein the characteristic of interest represents at least one of a boundary of the 001 or a ratio of dimensions for the OOI.

8. The method of claim 1, wherein the adjust operation includes adjusting at least one of a size or contour of the candidate shape based on characteristics of interest in the secondary reference frames.

9. The method of claim 1, further comprising calculating a volume for the resultant shape.

10. The method of claim 1, wherein the OOI is a bladder, a stomach, a kidney or a liver.

11. A mobile ultrasound imaging system comprising:

a portable host system having one or more processors and a memory for storing a plurality of applications that include corresponding programmed instructions, wherein when a select application is activated the one or more processors execute programmed instructions of the select application by performing the following operations;

obtain a set of frames of 2D ultrasound images;

develop a prospect model indicating a likelihood that frames within the set include an organ of interest (OOI);

identify primary and secondary reference frames from the set of the frames based on the prospect model;

determine a characteristic of interest in the primary reference frame;

select a candidate shape for the OOI based on the character of interest in the primary reference frame; and

adjust the candidate shape based on the secondary reference frames to form a resultant shape for the OOI.

12. The mobile ultrasound imaging system of claim 11, wherein the identify operation includes identifying, from the set of frames, an ultrasound image that intersects a center of the OOI, the ultrasound image representing the primary reference frame.

13. The mobile ultrasound imaging system of claim 11, wherein the identify operation includes identifying, from the set of frames, ultrasound images intersects intermediate and peripheral edges of the OOI, the ultrasound images representing the primary and secondary reference frames.

14. The mobile ultrasound imaging system of claim 11, wherein the develop operation includes identifying a pixel pattern between adjacent frames in the set of frames and deriving the prospect model based on the pixel pattern.

15. The mobile ultrasound imaging system of claim 11, wherein the develop operation includes identifying regions of interest in adjacent frames in the set of frames, calculating pixel intensity information for the regions of interest, and deriving the prospect model based on the pixel intensity information.

16. The mobile ultrasound imaging system of claim 11, wherein the develop operation includes determining tilt angle information regarding for at least a portion of the set of frames, and deriving the prospect model based on the tilt angle information.

17. The mobile ultrasound imaging system of claim 11, wherein the characteristic of interest represents at least one of a boundary of the OOI or a ratio of dimensions for the OOI.

18. The mobile ultrasound imaging system of claim 11, wherein the adjust operation includes adjusting at least one of a size or contour of the candidate shape based on characteristics of interest in the secondary reference frames.

19. The mobile ultrasound imaging system of claim 11, further comprising calculating a volume for the resultant shape.

20. A tangible and non-transitory computer readable medium comprising one or more programmed instructions configured to direct one or more processors to:

obtain a set of frames of 2D ultrasound images;

develop a prospect model indicating a likelihood that frames within the set include an organ of interest (OOI);

identify primary and secondary reference frames from the set of the frames based on the prospect model;

determine a characteristic of interest in the primary reference frame;

select a candidate shape for the OOI based on the character of interest in the primary reference frame; and

adjust the candidate shape based on the secondary reference frames to form a resultant shape for the OOI.