METHOD OF PROCESSING SPATIAL-TEMPORAL DATA PROCESSING

• US 20080021945A1
• Filed: 07/20/2007
• Published: 01/24/2008
• Est. Priority Date: 07/20/2006
• Status: Abandoned Application

• Current Assignee: Ultrasound Medical Devices, Inc.
• Original Assignee: Ultrasound Medical Devices, Inc.
• Inventors: O'Donnell, Matthew, Hamilton, James
• Application Number:
  US11/781,223
• Publication Number:
  US 20080021945A1
• Time in Patent Office: Days
• US Class Current: 708/300
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 7/251 involving models
• CPC Class Codes: G06T 7/277 involving stochastic approaches, e.g. using Kalman filters

Abstract

In one embodiment, the invention includes a method of formulating a parametric model from spatial-temporal data including fitting model parameters calculated from spatial-temporal data to at least one displacement model and calculating new spatial temporal data based on the model. In another embodiment, the invention includes a method of processing spatial-temporal data including filtering the spatial temporal data and assessing data quality based on data quality metrics.

Claims

1. A method of processing spatial-temporal data comprising:

filtering the spatial-temporal data; and

assessing data quality based on a data quality metric.

2. The method of claim 1 wherein the step of filtering the spatial-temporal data includes temporal filtering.

3. The method of claim 2 wherein the spatial-temporal data is filtered with at least one filter selected from the group consisting of:

Finite Impulse Response Filter and Infinite Impulse Response Filter.

4. The method of claim 3 wherein the Finite Impulse Response Filter includes space-time filtering.

5. The method of claim 4 wherein the space-time filtering is performed with at least one method selected from the group consisting of:

3-D kernel convolution and 3-D Fourier transform multiplication.

6. The method of claim 1 wherein the step of filtering the spatial-temporal data includes a Kalman filter.

7. The method of claim 1 wherein the step of assessing data quality includes at least one method selected from the group consisting of:

sample elimination, sample interpolation, sample weighting, sample thresholding, and a combination of sample weighting and sample thresholding.

8. The method of claim 7 wherein the step of assessing data quality includes assessing data quality based on at least one data quality metric selected from the group consisting of:

peak correlation, spatial and temporal variation of displacement, and spatial and temporal variations of correlation magnitude.

9. The method of claim 1 wherein the step of assessing data quality includes assessing data quality based on at least one data quality metric selected from the group consisting of:

peak correlation, spatial and temporal variation of displacement, and spatial and temporal variations of correlation magnitude.

10. The method of claim 1 wherein the spatial-temporal data is a real-time datastream.

11. The method of claim 1 wherein the spatial-temporal data is a stored datastream.

12. The method of claim 1 wherein the spatial-temporal data includes acoustic frames.

13. The method of claim 1 wherein the spatial-temporal data includes scan converted images.

14. A method of formulating a parametric model from spatial-temporal data comprising:

fitting model parameters calculated from spatial-temporal data to at least one displacement model; and

calculating new spatial temporal data based on the model.

15. The method of claim 14, further comprising the step of assessing data quality based on data quality metrics.

16. The method of claim 14 wherein the step of evaluating data quality includes at least one method selected from the group consisting of:

sample elimination, sample interpolation, sample weighting, sample thresholding, or a combination of sample weighting and sample thresholding.

17. The method of claim 14 wherein the spatial-temporal data is a real-time datastream.

18. The method of claim 14 wherein the spatial-temporal data is a stored datastream.

19. The method of claim 14 wherein the spatial-temporal data includes acoustic frames.

20. The method of claim 14 wherein the spatial-temporal data includes scan converted images.