# US 10,499,867 B2 · Method, storage medium, and system for analyzing image sequences of periodic physiological activities > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,499,867 B2 - Document ID: US10499867B2 - Status: Granted - Kind: B2 - Application number: 15/864,398 - Filed: 2018-01-08 - Published: 2019-07-11 - Granted: 2019-12-10 - Earliest claimed: 2018-01-08 - Assignees: Shenzhen Keya Medical Technology Corporation - Applicants: Shenzhen Keya Medical Technology Corporation - Inventors: Xiaoxiao Liu; Shubao Liu; Bin Ma; Kunlin Cao; Youbing Yin; Yuwei Li; Qian Zhao; Qi Song - Web page: https://patentgrep.com/patent/US10499867B2 ## CPC - A61B 6/504: {for diagnosis of blood vessels, e.g. by angiography} - A61B 6/5217: {extracting a diagnostic or physiological parameter from medical diagnostic data} - G06F 16/535: Filtering based on additional data, e.g. user or group profiles - G06T 7/0012: {Biomedical image inspection} - G06T 7/0016: {involving temporal comparison} - G06T 7/20: Analysis of motion (motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51) - G06T 7/269: using gradient-based methods - G06T 7/277: involving stochastic approaches, e.g. using Kalman filters - G16H 50/30: for calculating health indices; for individual health risk assessment - A61B 6/5264: {due to motion} - G06F 16/50: of still image data - G06T 2207/10081: Computed x-ray tomography [CT] - G06T 2207/30004: Biomedical image processing - G06T 2207/30048: Heart; Cardiac - G06T 2207/30101: Blood vessel; Artery; Vein; Vascular - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## 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. ## Claims ### Claim 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. ### Claim 2 (depends on 1) The method of claim 1, wherein determining the local motions includes calculating a local motion vector for each pixel. ### Claim 3 (depends on 2) 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. ### Claim 4 (depends on 1) The method of claim 1, wherein determining the principal motions includes' calculating a principal motion vector using a principal components analysis. ### Claim 5 (depends on 4) 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. ### Claim 6 (depends on 1) 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. ### Claim 7 (depends on 6) 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. ### Claim 8 (depends on 1) The method of claim 1, wherein the periodic physiological activity includes a cardiac activity or a respiratory activity. ### Claim 9 (depends on 6) 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. ### Claim 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. ### Claim 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. ### Claim 12 (depends on 11) 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. ### Claim 13 (depends on 12) 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. ### Claim 14 (depends on 12) The system of claim 12, further comprising: a display configured to display the frames marked with the phases.