SINGULAR VALUE FILTER FOR IMAGING OR DETECTION

• US 20130094729A1
• Filed: 10/12/2012
• Published: 04/18/2013
• Est. Priority Date: 10/12/2011
• Status: Active Grant

• Current Assignee: University of Virginia Patent Foundation (University of Virginia)
• Original Assignee: University of Virginia Patent Foundation (University of Virginia)
• Inventors: Mauldin, F. William Jr., Hossack, John A,, Patil, Abhay V.
• Granted Patent: US 9,002,080 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: A61B 8/0891 for diagnosis of blood vessels
• CPC Class Codes: A61B 8/481 involving the use of contrast agent, e.g. microbubbles introduced into the bloodstream analysis of echo signal exploiting properties of a contrast enhancer in devices for short-range imaging with acoustic waves G01S7/52039
• CPC Class Codes: A61B 8/485 involving measuring strain or elastic properties
• 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: G01S 15/8915 using a transducer array
• CPC Class Codes: G01S 15/8981 Discriminating between fixed and moving objects or between objects moving at different speeds, e.g. wall clutter filter
• CPC Class Codes: G01S 7/52039 exploiting the non-linear response of a contrast enhancer, e.g. a contrast agent diagnostic techniques involving the use of contrast agents A61B8/481
• CPC Class Codes: G01S 7/52041 detecting modification of a contrast enhancer, e.g. detecting the destruction of a contrast agent by an acoustic wave, e.g. loss of correlation diagnostic techniques involving the use of contrast agents A61B8/481
• CPC Class Codes: G01S 7/52042 determining elastic properties of the propagation medium or of the reflective target diagnostic techniques involving the measurement of strain A61B8/485
• CPC Class Codes: G01S 7/52046 Techniques for image enhancement involving transmitter or receiver image enhancement by image data processing G06T5/00
• CPC Class Codes: G06F 18/2135 based on approximation criteria, e.g. principal component analysis

Abstract

Apparatus or techniques can include obtaining information indicative of energy, such as ultrasonic energy, reflected from a tissue region, forming respective input matrices representative of the obtained information, the input matrices respectively comprising an ensemble-of-interest and at least one ensemble corresponding to a spatial location nearby a spatial location corresponding to the ensemble-of-interest, performing respective singular value decompositions on the respective input matrices to obtain respective sets of singular values corresponding to respective sets of singular vectors, obtaining respective output matrices including weighting a respective projection of a respective ensemble-of-interest onto at least one of the singular vectors included in a respective set of singular vectors, and, using the respective output matrices, at least one of determining a characteristic, or constructing an image, of at least a portion of the tissue region.

Claims

1. A system for use with a transducer array, the transducer array configured to deliver energy to a tissue region, the system comprising:

a processor circuit configured to;

obtain, using the transducer array, information indicative of the delivered energy reflected from the tissue region;

form respective input matrices representative of the obtained information indicative of the energy reflected from the tissue region, the respective input matrices including information corresponding to a spatial dimension and a temporal dimension, the input matrices respectively comprising an ensemble-of-interest and at least one ensemble corresponding to a spatial location nearby a spatial location corresponding to the ensemble-of-interest;

perform respective singular value decompositions on the respective input matrices to obtain respective sets of singular values corresponding to respective sets of singular vectors;

obtain respective output matrices including weighting a respective projection of a respective ensemble-of-interest onto at least one of the singular vectors included in a respective set of singular vectors; and

using the respective output matrices, at least one of determine a characteristic, or construct an image, of at least a portion of the tissue region.

2. The system of claim 1, wherein the processor circuit is configured to obtain a respective output matrix including using an adaptively determined weighting function.

3. The system of claim 2, wherein the processor circuit is configured to adaptively determine at least one respective weighting function for each respective output matrix, each respective output matrix corresponding to a respective input matrix.

4. The system of claim 2, wherein the weighting function varies continuously between 0 and 1 without a discontinuity.

5. The system of claim 4, wherein the weighting function includes a modified sigmoidal weighting function.

6. The system of claim 2, wherein the weighting function is adaptively determined using information about at least one of the respective singular values.

7. The system of claim 2, wherein the weighting function is adaptively determined at least in part using information about a motion complexity of a target in the tissue region.

8. The system of claim 2, wherein the weighting function is adaptively determined to suppress or eliminate at least one of a clutter artifact or noise.

9. The system of claim 1, wherein the processor circuit is configured to determine a characteristic at least a portion of the tissue region using the respective output matrices.

10. The system of claim 9, wherein the characteristic includes a motion of a target located within the tissue region.

11. The system of claim 1, wherein the ensemble-of-interest includes information corresponding to a depth dimension with respect to a transducer plane and a temporal dimension.

12. The system of claim 1, wherein the processor circuit is configured to construct an image of at least a portion of the tissue region using the respective output matrices.

13. The system of claim 12, wherein the respective ensembles-of-interest correspond to respective pixels included in an image frame;

and

wherein the processor circuit is configured to construct the image by determining a filtered output matrix corresponding to respective pixels in the image frame using the respective weightings and the respective singular value decompositions.

14. The system of claim 1, wherein the obtained information includes complex-valued samples of the echo information represented by real and imaginary parts;

and

wherein the respective input matrices comprise complex-valued elements represented by real and imaginary parts.

15. The system of claim 1, further comprising an ultrasonic transducer array. configured to insonify the region of tissue using ultrasonic energy;

and

wherein the obtained information indicative of the energy reflected from the tissue region comprises ultrasonic energy reflected from the insonified region.

16. A system for use with a transducer array, the transducer array configured to deliver energy to a tissue region, the system comprising:

a processor circuit configured to;

obtain, from the transducer array, information indicative of the delivered energy reflected from the tissue region;

form respective input matrices representative of the obtained information indicative of the energy reflected from the tissue region, the respective input matrices including information corresponding to a spatial dimension and a temporal dimension, the input matrices respectively comprising an ensemble-of-interest and at least one ensemble corresponding to a spatial location nearby a spatial location corresponding to the ensemble-of-interest;

perform respective singular value decompositions on the respective input matrices to obtain respective sets of singular values corresponding to respective sets of singular vectors;

obtain respective output matrices including weighting a respective projection of a respective ensemble-of-interest onto at least one of the singular vectors included in a respective set of singular vectors using a weighting function, including adaptively determining the weighting function using information about at least one of the respective singular values; and

using the respective output matrices, at least one of determine a characteristic, or construct an image, of at least a portion of the tissue region;

wherein the weighting function;

varies continuously between 0 and 1 without a discontinuity;

and

includes a modified sigmoidal weighting function.

17. A method, comprising:

obtaining, from a transducer array, information indicative of the delivered energy reflected from the tissue region;

forming respective input matrices representative of the obtained information indicative of the energy reflected from the tissue region, the respective input matrices including information corresponding to a spatial dimension and a temporal dimension, the input matrices respectively comprising an ensemble-of-interest and at least one ensemble corresponding to a spatial location nearby a spatial location corresponding to the ensemble-of-interest;

performing respective singular value decompositions on the respective input matrices to obtain respective sets of singular values corresponding to respective sets of singular vectors;

obtaining respective output matrices including weighting a respective projection of a respective ensemble-of-interest onto at least one of the singular vectors included in a respective set of singular vectors; and

using the respective output matrices, at least one of determining a characteristic, or constructing an image, of at least a portion of the tissue region.

18. The method of claim 17, comprising obtaining a respective output matrix including weighting the respective projection using a weighting function using an adaptively determined weighting function.

19. The method of claim 18, comprising adaptively determining at least one respective weighting function for each respective output matrix, each respective output matrix corresponding to a respective input matrix.

20. The method of claim 18, wherein the weighting function varies continuously between 0 and 1 without a discontinuity.