# US 10,863,950 B2 · Methods and systems for retrospective internal gating > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,863,950 B2 - Document ID: US10863950B2 - Status: Granted - Kind: B2 - Application number: 16/395,201 - Filed: 2019-04-25 - Published: 2019-11-21 - Granted: 2020-12-15 - Earliest claimed: 2007-05-04 - Assignees: Memorial Sloan Kettering Cancer Center - Applicants: Memorial Sloan Kettering Cancer Center - Inventors: Adam L. Kesner - Web page: https://patentgrep.com/patent/US10863950B2 ## CPC - A61B 6/032: {Transmission computed tomography [CT]} - A61B 6/037: {Emission tomography} - A61B 6/527: {using data from a motion artifact sensor} - A61B 5/7289: {Retrospective gating, i.e. associating measured signals or images with a physiological event after the actual measurement or image acquisition, e.g. by simultaneously recording an additional physiological signal during the measurement or image acquisition} - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract The present invention, in one form, is a method for deriving respiratory gated PET image reconstruction from raw PET data. In reconstructing the respiratory gated images in accordance with the present invention, respiratory motion information derived from individual voxel signal fluctuations, is used in combination to create usable respiratory phase information. Employing this method allows the respiratory gated PET images to be reconstructed from PET data with out the use of external hardware, and in a fully automated manner. ## Claims ### Claim 1 A method for retrospective internal gating comprising: acquiring image data corresponding to times t1 . . . tn to be used to generate one or more images corresponding to a moving object; extracting information for a plurality of arrays derived from the image data; generating a time varying object motion function based on the extracted information for the plurality of arrays of the image data; determining, using the time varying object motion function, phase information for motion of the moving object; and generating at least one image correcting for the motion of the moving object using the determined phase information for motion of the moving object and the acquired image data. ### Claim 2 (depends on 1) The method of claim 1, wherein information is defined as a signal of an array element over times t1 . . . tn. ### Claim 3 (depends on 1) The method of claim 1, further comprising assigning weighting factors to the plurality of arrays, wherein the weighting factors include array specific weighting factors based on the mean array activity over times t1 . . . tn. ### Claim 4 (depends on 1) The method of claim 1, further comprising assigning weighting factors to the plurality of arrays, wherein the weighting factors include array specific weighting factors based upon the array's proximity to greater spatial signal gradients on a non-corrected image. ### Claim 5 (depends on 4) The method of claim 4, wherein the non-corrected image is comprised of combined image data from times t1 . . . tn. ### Claim 6 (depends on 1) The method of claim 1, further comprising assigning weighting factors to the plurality of arrays, wherein the weighting factors include array specific weighting factors assigned based on magnitude of signal variation over times t1 . . . tn, for each array. ### Claim 7 (depends on 1) The method of claim 1, wherein at least some arrays of the plurality of arrays are deemed unimportant and weighted at zero usage value. ### Claim 8 (depends on 1) The method of claim 1, wherein information is filtered in frequency space for windows encompassing expected valid periodicity of the motion. ### Claim 9 (depends on 8) The method of claim 8, wherein the frequency window used may be adjusted to be patient or data specific. ### Claim 10 (depends on 8) The method of claim 8, wherein the frequency window may be adjusted over times t1 . . . tn. ### Claim 11 (depends on 1) The method of claim 1, wherein array information is processed serially in order of prioritization to yield a time varying object motion function. ### Claim 12 (depends on 11) The method of claim 11, wherein the time varying object motion function spans t1 . . . tn. ### Claim 13 (depends on 1) The method of claim 1, wherein the initial time varying object motion function is assigned to be the curve of the array with the highest priority. ### Claim 14 (depends on 1) The method of claim 1, wherein individual array information is combined with the evolving time varying object motion function in three possible scenarios: the first scenario is leaving the current time varying object motion function unaltered, the second scenario is adding the individual array information to the current time varying object motion function, and the third scenario is subtracting the individual array information from the current time varying object motion function, to account for possible phase mismatch; of these three scenarios, the one with the most significant improvement is chosen as the new time varying object motion function, to be used in evaluation of the next voxel. ### Claim 15 (depends on 1) The method of claim 1, further comprising assigning weighting factors to the plurality of arrays. ### Claim 16 (depends on 1) The method of claim 1, wherein determining, using the time varying object motion function, the phase information for motion of the moving object is based upon identifying non-recurring patterns in the time varying object motion function. ### Claim 17 (depends on 1) The method of claim 1, wherein the determining, using the time varying object motion function, the phase information for motion of the moving object is based upon identifying recurring patterns in the time varying object motion function. ### Claim 18 (depends on 1) The method of claim 1, further comprising mapping of image data to corresponding motion phases using the time varying object motion function, wherein mapped image data is reordered and categorized in such a way that images within a category all appear to be taken at the same phase of motion. ### Claim 19 (depends on 1) The method of claim 1, wherein the acquired data includes data for a respiratory cycle of a subject corresponding to the moving object. ### Claim 20 (depends on 1) The method of claim 1, wherein acquiring the image data includes acquiring the image data for a greater amount of time than one breath cycle of a subject corresponding to the moving object. ### Claim 21 A non-transitory computer-readable medium encoded with a program that when executed by one or more processors cause a machine to: acquire image data corresponding to times t1 . . . tn to be used to generate one or more images corresponding to a moving object; extract information for a plurality of arrays derived from the image data; generate a time varying object motion function based on the extracted information for the plurality of arrays of the image data; determine, using the time varying object motion function, phase information for motion of the moving object; and generate at least one image correcting for the motion of the moving object using the determined phase information for motion of the moving object and the acquired image data. ### Claim 22 A system comprising: one or more processors; and a non-transitory computer-readable medium having instructions stored thereon that when executed by the one or more processors cause the system to: acquire image data corresponding to times t1 . . . tn to be used to generate one or more images corresponding to a moving object; extract information for a plurality of arrays derived from the image data; generate a time varying object motion function based on the extracted information for the plurality of arrays of the image data; determine, using the time varying object motion function, phase information for motion of the moving object; and generate at least one image correcting for the motion of the moving object using the determined phase information for motion of the moving object and the acquired image data.