System and method to identify and measure organ wall boundaries

• US 7,819,806 B2
• Filed: 01/22/2007
• Issued: 10/26/2010
• Est. Priority Date: 06/07/2002
• Status: Active Grant

• Current Assignee: Verathon Incorporated (Roper Technologies, Inc.)
• Original Assignee: Verathon Incorporated (Roper Technologies, Inc.)
• Inventors: Dudycha, Stephen, McMorrow, Gerald, Yang, Fuxing
• Primary Examiner(s): Casler; Brian
• Assistant Examiner(s): Lamprecht; Joel M
• Application Number:
  US11/625,805
• Publication Number:
  US 20070276254A1
• Time in Patent Office: 1,373 Days
• Field of Search: 600/437, 600/443, 600/449, 600/447, 736/25, 736/26
• US Class Current: 600/437
• 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 5/418 lymph vessels, ducts or nodes
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 8/08 Detecting organic movements or changes, e.g. tumours, cysts, swellings A61B8/02 - A61B8/06 take precedence
• CPC Class Codes: A61B 8/0858 involving measuring tissue layers, e.g. skin, interfaces
• CPC Class Codes: A61B 8/4427 Device being portable or laptop-like
• CPC Class Codes: A61B 8/4455 Features of the external shape of the probe, e.g. ergonomic aspects
• CPC Class Codes: A61B 8/4472 Wireless probes
• CPC Class Codes: A61B 8/4483 characterised by features of the ultrasound transducer
• CPC Class Codes: A61B 8/461 Displaying means of special interest
• CPC Class Codes: A61B 8/467 characterised by special input means
• CPC Class Codes: A61B 8/469 for selection of a region of interest
• CPC Class Codes: A61B 8/483 involving the acquisition of a 3D volume of data
• CPC Class Codes: A61B 8/565 involving data transmission via a network
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/20101 Interactive definition of point of interest, landmark or seed
• CPC Class Codes: G06T 2207/20116 Active contour; Active surface; Snakes
• CPC Class Codes: G06T 2207/20161 Level set
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 7/0012 : Biomedical image inspection
• CPC Class Codes: G06T 7/12 : Edge-based segmentation
• CPC Class Codes: G06T 7/149 : involving deformable models, e.g. active contour models

Abstract

Systems and methods are described for acquiring, processing, and presenting boundaries of a cavity-tissue interface within a region-of-interest in an ultrasound image based upon the strength of signals of ultrasound echoes returning from structures within the region-of-interest. The segmentation of boundaries of cavity shapes occupying the region-of-interest utilizes cost function analysis of pixel sets occupying the cavity-tissue interface. The segmented shapes are further image processed to determine areas and volumes of the organ or structure containing the cavity within the region-of-interest.

Claims

1. A method for processing ultrasonic imaging information of a region-of-interest within a subject derived from signals of ultrasound echoes captured by an ultrasonic transceiver placed against a surface location of the patient, the method comprising:

presenting a Cartesian or X-axis stretched polar image of the cavity on a display in proportion to the strength of signals derived from fundamental or harmonic ultrasound echoes;

enhancing the Cartesian or X-axis stretched polar image;

selecting within the enhanced Cartesian or X-axis stretched polar image pixel candidate sets occupying regions near a cavity-tissue interface utilizing either a fast marching live wire algorithm or a level set active contour algorithm; and

determining a boundary contour between the cavity-tissue interface based upon extracting positional information from a cost function analysis of pixels in the image pixel candidate sets when selection of the pixel candidate sets is by the fast marching live wire algorithm or by the deformation of the boundary contour presented by the pixel candidate sets when selection is made by the level set active contour algorithm; and

displaying the enhanced Cartesian or X-axis stretched polar image.

2. The method of claim 1, wherein enhancing the image includes using at least one of intensity-based segmentation, edge-based segmentation, and anisotropic diffusion.

3. The method of claim 1, wherein selecting pixel candidate sets for processing by the fast marching live wire algorithm includes creating radial vectors projecting from pixel candidate sets positioned near the boundary contour aligned within a 2D image.

4. The method of claim 1, wherein selecting pixel candidate sets for processing by the fast marching live wire algorithm or the level set active contour algorithm includes pixel candidate sets positioned near the front wall and the back wall of the boundary contour.

5. The method of claim 1, wherein determining the boundary contour between the cavity-tissue interface based upon extracting positional information from the cost function analysis includes defining a final cost of a computed gradient value for a pixel candidate and an intensity factor for an optimal path in the boundary contour.

6. A system for ultrasonic imaging of a region-of-interest within a subject derived from signals of ultrasound echoes captured by an ultrasonic transceiver placed against a surface location of the patient, the system comprising:

a microprocessor device having a display, the microprocessor device configured to present a Cartesian or X-axis stretched polar image of the cavity on the display in proportion to the strength of signals derived from fundamental or harmonic ultrasound echoes; and

a non-transitory computer readable medium having instructions executable by the microprocessor device to

enhance the Cartesian or X-axis stretched polar image using at least one of intensity-based segmentation, edge-based segmentation, and anisotropic diffusion;

select within the enhanced Cartesian or X-axis stretched polar image pixel candidate sets occupying regions near a cavity-tissue interface utilizing either a fast marching live wire algorithm or a level set active contour algorithm; and

determine a boundary contour between the cavity-tissue interface based upon extracting positional information from a cost function analysis of pixels in the image pixel candidate sets when selection of the pixel candidate sets is by the fast marching live wire algorithm or by the deformation of the boundary contour presented by the pixel candidate sets when selection is made by the level set active contour algorithm.

7. The system of claim 6, wherein the pixel candidate sets are positioned near the front wall and the back wall of the boundary contour.