Linear-Based Eulerian Motion Modulation

• US 20140072190A1
• Filed: 03/26/2013
• Published: 03/13/2014
• Est. Priority Date: 09/07/2012
• Status: Active Grant

• Current Assignee: Massachusetts Institute of Technology, Quanta Computer
• Original Assignee: Massachusetts Institute of Technology
• Inventors: Rubinstein, Michael, Guttag, John V., Freeman, William T., Wu, Hao-yu, Shih, Eugene Inghaw, Durand, Frederic
• Granted Patent: US 9,811,901 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 2207/30076 Plethysmography
• CPC Class Codes: G06T 2207/30088 Skin; Dermal
• CPC Class Codes: G06T 2207/30104 Vascular flow; Blood flow; Perfusion
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/0016 involving temporal comparison
• CPC Class Codes: G06T 7/254 involving subtraction of images
• CPC Class Codes: G06T 7/262 using transform domain methods, e.g. Fourier domain methods

Abstract

In one embodiment, a method of amplifying temporal variation in at least two images comprises examining pixel values of the at least two images. The temporal variation of the pixel values between the at least two images can be below a particular threshold. The method can further include applying signal processing to the pixel values.

Claims

1. A method of amplifying temporal variation in at least two images, the method comprising:

examining pixel values of the at least two images, the temporal variation of the pixel values between the at least two images being below a particular threshold;

applying signal processing to the pixel values.

2. The method of claim 1, wherein applying signal processing amplifies the variations of the pixel values between the at least two images.

3. The method of claim 1, wherein the signal processing is temporal processing.

4. The method of claim 3, wherein the temporal processing is a bandpass filter.

5. The method of claim 4, wherein the bandpass filter is configured to analyze frequencies over time.

6. The method of claim 1, wherein applying signal processing includes spatial processing.

7. The method of claim 6, wherein the spatial processing removes noise.

8. The method of claim 1, further comprising visualizing a pattern of flow of blood in a body shown in the at least two images.

9. A system for amplifying temporal variation in at least two images, the system comprising:

a pixel examination module configured to examine pixel values of the at least two images, the temporal variation of the pixel values between the at least two images being below a particular threshold;

a signal processing module configured to apply signal processing to the pixel values.

10. The system of claim 9, wherein the signal processing module is further configured to amplify variations of the pixel values between the at least two images.

11. The system of claim 9, wherein the signal processing is temporal processing.

12. The system of claim 11, wherein the temporal processing is a bandpass filter.

13. The system of claim 12, wherein the bandpass filter is configured to analyze frequencies over time.

14. The system of claim 9, wherein applying signal processing includes spatial processing.

15. The system of claim 14, wherein the spatial processing removes noise.

16. The system of claim 9, further comprising a blood flow visualization module configured to visualize a pattern of flow of blood in a body shown in the at least two images.