Method and apparatus for composition and display of three-dimensional image from two-dimensional ultrasound scan data

• US 6,059,727 A
• Filed: 04/13/1998
• Issued: 05/09/2000
• Est. Priority Date: 06/15/1995
• Status: Expired due to Term

• Current Assignee: Board of Regents of the University of Michigan (University of Michigan)
• Original Assignee: Board of Regents of the University of Michigan (University of Michigan)
• Inventors: Carson, Paul L., Moskalik, Aaron, Fowlkes, J. Brian, Chen, Jian-Feng, Rubin, Jonathan M.
• Primary Examiner(s): Lateef, Marvin M.
• Assistant Examiner(s): Imam, Ali M.
• Application Number:
  US08/981,058
• Time in Patent Office: 757 Days
• Field of Search: 128/916, 600/443, 600/455, 600/456, 600/442, 356/28.5
• US Class Current: 600/443
• 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 8/14 Echo-tomography
• CPC Class Codes: G01S 15/8936 using transducers mounted for mechanical movement in three dimensions
• CPC Class Codes: G01S 15/8993 Three dimensional imaging systems
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 7/32 using correlation-based methods
• CPC Class Codes: Y10S 128/916 Ultrasound 3-D imaging

Abstract

A 3D image data set representing a volume of material such as human tissue is created using speckle decorrelation techniques to process successive 2D data slices from a moving, standard 1D or 1.5D ultrasound transducer. This permits the use of standard ultrasound machinery, without the use of additional slice-position hardware, to create 3D images without having to modify the machinery or its operation. Similar techniques can be used for special data processing within the imaging system as well to expedite the image acquisition process. Optionally, the image quality of 2D images can be enhanced through the use of multiple 3D data sets derived using the method.

Claims

1. A methods executed by a machine, of displaying a 3D image of a human tissue volume, said method comprising:

(a) receiving a plurality of data sets, referred to as data slices, each said data slice representing a respective 2D slice of said tissue volume, said plurality of data slices having been generated by ultrasound scanning of said tissue volume;

(b) defining (1) one or more regions within one of said data slices, referred to as regions 1a, 1b, and so on, within data slice 1, and (2) one or more regions within another of said data slices, referred to as regions 2a, 2b, and so on, within data slice 2;

(c) performing a process of speckle decorrelation measurement to determine respective amounts of correlation between regions 1a and 2a, regions 1b and 2b, and so on;

(d) utilizing said respective amounts of correlation to compute a relative positional difference vector representative of a relative positional difference between data slice 1 and data slice 2;

(e) storing in a memory device (1) a representation of at least a portion of said data slice 1, (2) a representation of at least a portion of said data slice 2, and (3) said relative positional difference vector;

(f) computing, from said relative positional difference vector, a relative position of each of said data slice 1 and said data slice 2 within a 3D image of the material; and

(g) displaying said 3D image on a visual display.

14. A program storage device having encoded instructions for performing the method of any of claims 1 through 13.

2. A method, executed by a machine, of creating a memory containing a data structure encoding a series of two-dimensional representations of a material, said method comprising:

(a) receiving a plurality of data sets, referred to as data slices, each said data slice representing a respective slice of said material;

(b) defining (1) one or more regions within one of said data slices, referred to as one or more regions within data slice 1, and (2) one or more regions within another of said data slices, referred to as one or more regions within data slice 2;

(c) measuring respective amounts of correlation between said one or more regions within data slice 1 and said one or more regions within data slice 2;

(d) utilizing said respective amounts of correlation to compute a relative positional difference vector representative of a relative positional difference between data slice 1 and data slice 2; and

(e) writing to said memory (1) a representation of at least a portion of said data slice 1, (2) a representation of at least a portion of said data slice 2, and (3) said relative positional difference vector.

3. The method of claim 2, wherein at least some of said data slices are smaller in size than required to specify a two-dimensional image.

4. The method of claim 2, wherein said data slices are received from a scanhead having a position relative to the material, and further comprising determining said position by performing a computation utilizing respective portions of at least two of said data slices.

5. The method of claim 2, wherein said data slices are received from a scanhead that is being moved relative to the material at a rate referred to as a scanning rate, and further comprising determining, from respective portions of at least two of said data slices, one or more of (i) a total number of data slices to be acquired, and (ii) a desired scanning rate.

6. The method of claim 2, wherein:

(1) at least some of said plurality of data slices are generated by scanning at least a portion of said material with a beam of coherent energy; and

(2) said material comprises a plurality of energy scatterers.

7. The method of claim 6, wherein said energy scatterers reflect coherent energy in a speckled pattern.

8. The method of claim 2, further comprising:

(1) computing, from said relative positional difference vector, a relative position of each of said data slice 1 and said data slice 2 within a 3D image of the material; and

(2) displaying said 3D image on a visual display.

9. The method of claim 2, wherein said measurement of respective amounts of correlation is performed by a process of speckle decorrelation measurement.

10. The method of claim 2, wherein said 2D data slices are generated by an ultrasound scan of said material.

11. The method of claim 2, wherein said material is a tissue volume.

12. The method of claim 2, wherein

(1) said measurement of an amount of correlation between a first one of said one or more regions in data slice 1 and a region in data slice 2 is performed by (i) locating one of said one or more regions in data slice 2 that has a minimum decorrelation value, referred to as a minimum-decorrelation region, and (ii) determining two orthogonal in-plane components of a vector between said minimum-decorrelation region and said first one of said regions in data slice 1;

and

(2) said utilization of said amount of correlation is performed by utilizing, as said measurement of said amount of correlation, an out-of-plane component of said vector that is orthogonal to said in-plane components.

15. A machine containing a memory having a data structure created by the method of any of claims 2 through 12.

16. A method in accordance with claim 2, wherein said data slices are obtained using an imaging transducer.

17. A method in accordance with claim 16, further comprising:

determining that motion of said transducer has changed by detecting an increase in the correlation of at least one data slice relative to at least one other previously obtained data slice.

18. A method in accordance with claim 2, wherein said step of computing said relative positional difference vector comprises image processing to find regions of coherent speckle.

19. A method in accordance with claim 2, wherein said step of computing said relative positional difference vector comprises image processing to extract data which do not represent coherent speckle.

20. A method in accordance with claim 2, wherein said step of computing said relative positional difference vector comprises image processing to extract data which do not decorrelate rapidly.

21. A method in accordance with claim 2, wherein said step of computing said relative positional difference vector using characteristics of data in a data slice to predict the behavior in an out-of-plane direction to include data in the positioning of slices.

22. A method in accordance with claim 2, wherein said step of computing said relative positional difference vector comprises using characteristics of data in a data slice to predict the behavior in an out-of-plane direction to exclude data in the positioning of slices.

31. A method in accordance with claim 2, wherein said plurality of data sets include data slices from at least two different look directions.

32. A method in accordance with claim 31, wherein all but one of said plurality of data sets can include only one data slice.

33. A method in accordance with claim 32, further comprising the step (f) of spatially aligning said plurality of data sets.

34. A method in accordance with claim 33, further comprising the step (g) of refining said relative positional difference vectors between adjacent slices.

35. A method in accordance with claim 34, wherein said step (f) of spatial alignment further comprises the steps of:

(h) of cross-correlating comparisons of vertical lines between two data sets to locate a most likely intersection point of two data slices from said two data sets; and

(i) utilizing said intersection point to position said data sets.

13. A method, executed by a machine, of displaying a 3D image of a human tissue volume, said method comprising:

(a) receiving a plurality of data sets, referred to as data slices, each said data slice representing a respective 2D slice of said tissue volume;

(b) defining (1) one or more regions within one of said data slices, referred to as one or more regions within data slice 1, and (2) one or more regions within another of said data slices, referred to as one or more regions within data slice 2;

(c) performing a process of speckle decorrelation measurement to determine respective amounts of correlation between said one or more regions in data slice 1 and said one or more regions in data slice 2;

(d) utilizing said respective amounts of correlation to compute a relative positional difference vector representative of a relative positional difference between data slice 1 and data slice 2.

23. A method of generating image views of imaged material, which views reveal specific characteristics of said material, comprising:

(a) receiving a plurality of data sets, referred to as data slices, each data slice representing a respective 2-D image of said material;

(b) image processing said data slices to identify regions of coherent speckle therein;

(c) generating said image views using slices having regions of coherent speckle therein.

24. A method of generating image views of imaged material, which views reveal specific characteristics of said material, comprising:

(a) receiving a plurality of data sets, referred to as data slices, each data slice representing a respective 2-D image of said material;

(b) image processing said data slices to extract data which do not represent coherent speckle;

(c) generating said image views using said processed data slices.

26. A method in accordance with claim 24, wherein said step (b) of image processing to extract data which do not represent coherent speckle comprises detecting and subtracting data corresponding to reverberations.

29. A method as in any of claims 26, 27, or 28, further comprising the step (d) of generating image views using data slices and portions of data slices which are relatively free from artifacts.

30. A method as in any of claims 26, 27, or 28, further comprising the step (d) of generating image views using data slices which reveal desired characteristics of said imaged material.

25. A method of generating image views of imaged material, which views reveal specific characteristics of said material, comprising:

(a) receiving a plurality of data sets, referred to as data slices, each data slice representing a respective 2-D image of said material;

(b) image processing said data slices to assess decorrelation rates in 3-D;

(c) selecting data slices for said image views based on said assessed decorrelation rates.

27. A method in accordance with claim 25, wherein said step (c) of selecting data slices based on assessed decorrelation rates comprises assessing decorrelation rates in adjacent slices to identify sets of slices in which decorrelation rate corresponds to artifacts of multiple scattering, refraction, diffraction, or shadowing.

28. A method in accordance with claim 25, wherein said step (c) of selecting data slices based on assessed decorrelation rates comprises assessing decorrelation rates in adjacent slices to identify regions of adjacent slices decelerating more rapidly than remaining regions in said adjacent slices.