IP Library Granted Patent US 9,256,934
Granted Patent B2
US 9,256,934 · App. 14/009,584 · Granted Feb 9, 2016

Enhanced image reconstruction in photoacoustic tomography

Inventors: Huabei Jiang (Gainesville, FL); Lei Yao (Gainesville, FL)
Assignee: UNIVERSITY OF FLORIDA RESEARCH FOUNDATION, INC.
G06T7/0012A61B5/0095A61B5/72A61B8/13A61B8/5207
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Quick Facts
Patent No.
US 9,256,934
App. No.
14/009,584
Granted
Feb 9, 2016
Kind
B2
Abstract

Various embodiments of methods and systems are provided for image reconstruction in photoacoustic tomography. In one embodiment, among others, a method includes obtaining photoacoustic time-domain data; reconstructing an image from the photoacoustic time-domain data using total-variation minimization based photoacoustic tomography reconstruction; and providing the reconstructed image for rendering on a display device. In another embodiment, a system includes a computing device and an image reconstruction program executable in the computing device. The image reconstruction program includes logic that obtains photoacoustic time-domain data; logic that reconstructs an image from the photoacoustic time-domain data using total-variation minimization based photoacoustic tomography reconstruction; and logic that provides the reconstructed image for rendering on a display device.

Claims (35)

1. A method, comprising:

obtaining photoacoustic data;

reconstructing a reconstructed image from the photoacoustic data using total-variation minimization based photoacoustic tomography reconstruction, where the total-variation minimization based photoacoustic tomography reconstruction is based at least in part upon a functional including observed acoustic field data and computed acoustic field data and a penalty term based upon variation of absorbed energy density (Φ); and

providing the reconstructed image for rendering on a display device.

2. The method of claim 1 , where in the penalty term is given by

L (Φ)=∫√{square root over (ω Φ 2 |∇Φ| 2 +δ 2 )} dxdy.

3. The method of claim 1 , wherein the total-variation minimization based photoacoustic tomography reconstruction is complete when the functional satisfies a predefined threshold.

4. The method of claim 1 , wherein the total-variation minimization based photoacoustic tomography reconstruction is performed for a predefined number of iterations.

5. The method of claim 1 , wherein the total-variation minimization based photoacoustic tomography reconstruction compensates for an effect of ultrasonic transducer response.

6. The method of claim 5 , wherein a normalized acoustic pressure distribution is applied to compensate for the effect of ultrasonic transducer response.

7. The method of claim 1 , wherein the reconstructed image is rendered with a color scale indicating the absorbed energy density.

8. The method of claim 1 , wherein the photoacoustic data is photoacoustic time-domain data or photoacoustic frequency-domain data.

9. The method of claim 1 , wherein the total-variation minimization based photoacoustic tomography reconstruction includes a dual-meshing scheme with forward calculation of a first mesh and inverse calculation of a second mesh.

10. The method of claim 9 , wherein the second mesh is a course mesh including fewer nodes and elements than the first mesh.

11. A system, comprising:

at least one computing device;

an image reconstruction program executable in the at least one computing device, the image reconstruction program comprising:

logic that obtains photoacoustic data;

logic that reconstructs a reconstructed image from the photoacoustic data using total-variation minimization based photoacoustic tomography reconstruction, where the total-variation minimization based photoacoustic tomography reconstruction is based at least in part upon a functional including observed acoustic field data and computed acoustic field data and a penalty term based upon variation of absorbed energy density (Φ); and

logic that provides the reconstructed image for rendering on a display device.

12. The system of claim 11 , where in the penalty term is given by

L (Φ)=∫√{square root over (ω Φ 2 |∇Φ| 2 +δ 2 )} dxdy.

13. The system of claim 11 , wherein the total-variation minimization based photoacoustic tomography reconstruction is complete when the functional satisfies a predefined threshold.

14. The system of claim 11 , wherein the total-variation minimization based photoacoustic tomography reconstruction is performed for a predefined number of iterations.

15. The system of claim 11 , wherein the total-variation minimization based photoacoustic tomography reconstruction compensates for an effect of ultrasonic transducer response.

16. The system of claim 15 , wherein a normalized acoustic pressure distribution is applied to compensate for the effect of ultrasonic transducer response.

17. A system, comprising:

at least one computing device;

an image reconstruction program executable in the at least one computing device, the image reconstruction program comprising:

logic that obtains photoacoustic data;

logic that reconstructs a reconstructed image from the photoacoustic data using total-variation minimization based photoacoustic tomography reconstruction, where the total-variation minimization based photoacoustic tomography reconstruction includes a dual-meshing scheme with forward calculation of a first mesh and inverse calculation of a second mesh; and

logic that provides the reconstructed image for rendering on a display device.

18. The system of claim 17 , wherein the second mesh is a course mesh including fewer nodes and elements than the first mesh.

19. The system of claim 11 , wherein the photoacoustic data is obtained from memory.

20. The system of claim 11 , wherein the photoacoustic data is photoacoustic time-domain data or photoacoustic frequency-domain data.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 4, 2013
From: JIANG, HUABEI; YAO, LEI
To: UNIVERSITY OF FLORIDA RESEARCH FOUNDATION, INC.
Reel/Frame 031345/0376 →
Continuity (2)
Provisional Application 61473348 · Apr 8, 2011
Related Publication 20140029829A1 · Jan 30, 2014