# US 10,478,058 B2 · Speckle reduction in optical coherence tomography images > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,478,058 B2 - Document ID: US10478058B2 - Status: Granted - Kind: B2 - Application number: 15/528,080 - Filed: 2015-11-19 - Published: 2017-11-09 - Granted: 2019-11-19 - Earliest claimed: 2014-11-20 - Assignees: Agency for Science, Technology and Research; Topcon Corporation - Applicants: Agency for Science, Technology and Research; Kabushiki Kaisha Topcon - Inventors: Jun Cheng; Jiang Liu; Wing Kee Damon Wong; Masahiro Akiba - Web page: https://patentgrep.com/patent/US10478058B2 ## CPC - A61B 3/102: {for optical coherence tomography [OCT]} - A61B 3/0025: {characterised by electronic signal processing, e.g. eye models} - G01B 9/02082: {Caused by speckles} - G01B 9/02083: {characterised by particular signal processing and presentation} - G01B 9/02091: Tomographic interferometers, e.g. based on optical coherence - G06T 5/50: using two or more images, e.g. averaging or subtraction - G06T 5/70: Denoising; Smoothing - G06T 2207/10101: Optical tomography; Optical coherence tomography [OCT] - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G01B: MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract An optical coherence tomography (OCT) image composed of a plurality of A-scans of a structure is analyzed by defining, for each A-scan, a set of neighboring A-scans surrounding the A-slices scan. Following an optional de-noising step, the neighboring A-scans are aligned in the imaging direction, then a matrix X is formed from the aligned A-scans, and matrix completion is performed to obtain a reduced speckle noise image. ## Claims ### Claim 1 A computer-implemented method of enhancing an optical coherence tomography (OCT) image composed of a plurality of A-scans, each A-scan being indicative of a structure imaged in a predefined direction, the A-scans being grouped as one or more B-scans, the method comprising, for each A-scan: (a) defining a respective neighborhood comprising a set of A-scans surrounding said each A-scan, the set of A-scans forming a two-dimensional as viewed in the predefined direction; (b) aligning the set of A-scans in the respective neighborhood to said each A-scan of the respective neighborhood; (c) using the aligned A-scans to form a first matrix X, respective columns of the first matrix X being the aligned A-scans; and (d) seeking a second matrix which minimizes a cost function indicative of the difference between the first matrix X and the second matrix, the second matrix being constrained to obey a complexity constraint. ### Claim 2 (depends on 1) A method according to claim 1 in which the complexity constraint is that the second matrix is constrained to have a rank no higher than a predefined value. ### Claim 3 (depends on 1) A method according to claim 1 in which the complexity constraint is that, representing the second matrix as the sum of a low rank matrix L and a sparse matrix S, the complexity constraints being that the low rank matrix L is constrained to have a rank less than a first predetermined value, and the sparse matrix S is constrained to have a number of non-zero elements less than a second predetermined value. ### Claim 4 (depends on 1) A method according to claim 1 comprising a prior operation of noise reduction in the plurality of A-scans. ### Claim 5 (depends on 4) A method according to claim 4 in which the noise-reduction is a speckle reduction anisotropic diffusion algorithm. ### Claim 6 (depends on 1) A method according to claim 1 wherein operation (b) is performed by: defining a first A-scan group consisting of one or more A-scans including said each A-scan of the respective neighborhood; and for each neighbouring A-scan: (i) defining a second respective A-scan group, the second respective A-scan group consisting of one or more A-scans including the neighbouring A-scan; (ii) seeking a respective translation value which, if the one or more A-scans of the respective second A-scan group are translated in the predefined direction by the translation value, minimises a difference between the first A-scan group and the second A-scan group; and (iii) translating the neighbouring A-scan by the respective translation value. ### Claim 7 (depends on 6) A method according to claim 6 in which operation (b) is performed by a block matching algorithm. ### Claim 8 (depends on 7) A method according to claim 7 wherein the block matching algorithm is a diamond search algorithm. ### Claim 9 (depends on 7) A method according to claim 7, wherein the two-dimensional array is a rectangular region or an elliptical region. ### Claim 10 A computer system comprising a processor and a memory device configured to store program instructions operative, when performed by the processor, to cause the processor to perform a method of enhancing an optical coherence tomography (OCT) image composed of a plurality of A-scans, each A-scan being indicative of a structure imaged in a predefined direction, the A-scans being grouped as one or more B-scans, the method comprising, for each A-scan: (a) defining a respective neighborhood comprising a set of A-scans surrounding said each A-scan, the set of A-scans forming a two-dimensional array as viewed in the predefined direction; (b) aligning the set of A-scans the respective neighborhood to said each A-scan of the respective neighborhood; (c) using the aligned A-scans to form a first matrix X, respective columns of the first matrix X being the aligned A-scans; and (d) seeking a second matrix which minimizes a cost function indicative of the difference between the first matrix X and the second matrix, the second matrix being constrained to obey a complexity constraint. ### Claim 11 A non-transitory computer program product, storing program instructions operative, when performed by a processor, to cause the processor to perform a method of enhancing an optical coherence tomography (OCT) image composed of a plurality of A-scans, each A-scan being indicative of a structure imaged in a predefined direction, the A-scans being grouped as one or more B-scans, the method comprising, for each A-scan: (a) defining a respective neighborhood comprising of a set of A-scans surrounding said each A-scan, the set of A-scans forming a two-dimensional array as viewed in the predefined direction; (b) aligning the set of A-scans in the respective neighborhood to said each A-scan of the respective neighborhood; (c) using the aligned A-scans to form a first matrix X, respective columns of the first matrix X being the aligned A-scans; and (d) seeking a second matrix which minimizes a cost function indicative of the difference between the first matrix X and the second matrix, the second matrix being constrained to obey a complexity constraint.