Method, storage medium, and system for analyzing image sequences of periodic physiological activities

Patent metadata

Field	Value
Publication number	US-10499867-B2
Application number	US-201815864398-A
Country	US
Kind code	B2
Filing date	Jan 8, 2018
Priority date	Jan 8, 2018
Publication date	Dec 10, 2019
Grant date	Dec 10, 2019

Abstract

The present disclosure relates to a method, storage medium, and system for analyzing an image sequence of a periodic physiological activity. In one implementation, the method includes receiving the image sequence acquired by an imaging device, the image sequence having a plurality of frames and determining local motions for pixels in each frame of the image sequence. The local motion for a pixel may be determined using corresponding pixels in frames adjacent to the frame to which the pixel belongs. The method further includes determining principal motions for the plurality of frames based on the local motions; determining a motion magnitude profile based on the principal motions; and determining the phase of each frame in the image sequence based on the motion magnitude profile.

First claim

What is claimed is:

1. A computer-implemented method for analyzing an image sequence of a periodic physiological activity, the method comprising:
receiving the image sequence acquired by an imaging device, the image sequence having a plurality of frames;
determining local motions for pixels in each frame of the image sequence, wherein the local motion for a pixel is determined using corresponding pixels in frames adjacent to the frame to which the pixel belongs;
determining principal motions for the plurality of frames based on the local motions;
determining a motion magnitude profile based on the principal motions; and
determining the phase of each frame in the image sequence based on the motion magnitude profile.

2. The method of claim 1 , wherein determining the local motions includes calculating a local motion vector for each pixel.

3. The method of claim 2 , wherein calculating a local motion vector for each pixel comprises applying at least one of non-rigid matching, patch matching between adjacent frames, and optical flow estimation.

4. The method of claim 1 , wherein determining the principal motions includes' calculating a principal motion vector using a principal components analysis.

5. The method of claim 4 , further comprising:
identifying a subset of the local motions caused by non-physiological activity; and
excluding the subset from the principal components analysis.

6. The method of claim 1 , wherein determining the motion magnitude profile further includes calculating global motion magnitudes for the plurality of frames; and integrating the global motion magnitudes.

7. The method of claim 6 , wherein determining the phase of each frame comprises determining a global displacement for the frame, and determines a corresponding position of the global displacement on the global motion magnitude profile.

8. The method of claim 1 , wherein the periodic physiological activity includes a cardiac activity or a respiratory activity.

9. The method of claim 6 , wherein determining the phase of each frame is based on a zero-crossing and a slope on the global motion magnitude profile.

10. A non-transitory computer-readable storage medium, with computer-executable instructions stored thereon, wherein the instructions, when executed by a processor, cause the processor to perform a method for analyzing an image sequence of a periodic physiological activity, the method comprising:
receiving the image sequence acquired by an imaging device, the image sequence having a plurality of frames;
determining local motions for pixels in each frame of the image sequence, wherein the local motion for a pixel is determined using corresponding pixels in frames adjacent to the frame to which the pixel belongs;
determining principal motions for the plurality of frames based on the local motions;
determining a motion magnitude profile based on the principal motions; and
determining the phase of each frame in the image sequence based on the motion magnitude profile.

11. A system for performing analysis on an image sequence of periodic physiological activity, comprising:
a processor; and
a memory storing computer-executable instructions that, when executed by the processor, cause the processor to:
receive the image sequence acquired by an imaging device, the image sequence having a plurality of frames;
determine local motions for pixels in each frame of the image sequence, wherein the local motion for a pixel is determined using corresponding pixels in frames adjacent to the frame to which the pixel belongs;
determine principal motions for the plurality of frames based on the local motions;
determine a motion magnitude profile based on the principal motions; and
determine the phase of each frame in the image sequence based on the motion magnitude profile.

12. The system of claim 11 , wherein the instructions further comprise:
marking the calculated phases on corresponding frames, and
storing, in the memory, the frames marked with the phases.

13. The system of claim 12 , wherein the memory is in communication with a medical database storing at least one of the image sequence and the frames marked with the phases.

14. The system of claim 12 , further comprising:
a display configured to display the frames marked with the phases.

Assignees

• Shenzhen Keya Medical Tech Corporation

Inventors

• Liu Xiaoxiao
• Liu Shubao
• Ma Bin
• Cao Kunlin
• Yin Youbing
• Li Yuwei
• Zhao Qian
• Song Qi

Classifications

• G06T2207/30101

  Blood vessel; Artery; Vein; Vascular · CPC title

• G06T7/277 Primary

  involving stochastic approaches, e.g. using Kalman filters · CPC title

• G06T7/269

  using gradient-based methods · CPC title

• G06T7/0016

  involving temporal comparison · CPC title

• G06F16/535

  Filtering based on additional data, e.g. user or group profiles · CPC title