# US 12,223,751 B2 · Self-test for imaging device > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,223,751 B2 - Document ID: US12223751B2 - Status: Granted - Kind: B2 - Application number: 18/746,750 - Filed: 2024-06-18 - Published: 2024-12-05 - Granted: 2025-02-11 - Earliest claimed: 2021-12-20 - Assignees: 10x Genomics, Inc. - Applicants: 10x Genomics, Inc. - Inventors: Dongyao Li; William Nitsch; Neil Ira Weisenfeld; Reynaldo Farias Zorrilla; Pratomo Putra Alimsijah; Augusto Manuel Tentori; Ashkan Beyranvand Nejad; Denis Pristinski - Web page: https://patentgrep.com/patent/US12223751B2 ## CPC - G06T 7/337: {involving reference images or patches} - G06V 20/69: Microscopic objects, e.g. biological cells or cellular parts - G06T 7/80: Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration - G01B 21/042: {Calibration or calibration artifacts (G01B3/30, G01B9/02072 take precedence)} - G02B 21/34: Microscope slides, e.g. mounting specimens on microscope slides - G02B 21/365: {Control or image processing arrangements for digital or video microscopes (G02B21/361, G02B21/362 take precedence)} - G06T 2207/10004: Still image; Photographic image - G06T 2207/20104: Interactive definition of region of interest [ROI] - G06T 2207/30024: Cell structures in vitro; Tissue sections in vitro - G06T 2207/30168: Image quality inspection - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G01B: MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS - G02B: OPTICAL ELEMENTS, SYSTEMS OR APPARATUS ## Abstract A method of self-testing an imaging system of a sample handling apparatus is provided. Systems and non-transitory computer readable mediums performing the method are also provided. ## Claims ### Claim 1 A method of self-testing an imaging system of a sample handling apparatus, comprising: mounting a self-test slide within a sample handling apparatus including an imaging system, wherein the mounted self-test slide is positioned with respect to an image sensor of the imaging system, the self-test slide comprising a pattern positioned on an optically transparent substrate, wherein the pattern includes an array of first features and at least one second feature including a reference side, wherein the array of first features has a minimum linear density greater than or equal to four pixels, and wherein the reference side is rotated at a non-zero angle with respect to an edge of the image sensor; acquiring, by the image sensor, image data representing a single image of the pattern; receiving, by a data processor, the single image of the pattern; determining, by the data processor based upon the received single image of the pattern, at least one of a linear distortion error or a non-linear distortion error for an optical system; comparing, by the data processor, at least one of the determined linear distortion error or the non-linear distortion error to a corresponding registration error threshold; and outputting, by the data processor, a first annunciation when at least one of the determined linear distortion error or the non-linear distortion error is greater than or equal to the corresponding registration error threshold, and outputting, by the data processor, a second annunciation, different than the first annunciation, when the at least one of determined linear distortion error or the non-linear distortion error is less than the corresponding registration error. ### Claim 2 (depends on 1) The method of claim 1, further comprising: determining, by the data processor based upon the received single image of the pattern, both the linear distortion error and the non-linear distortion error for the optical system including the image sensor; comparing, by the data processor, both the determined linear distortion error and non-linear distortion error to a corresponding registration error threshold; and outputting the first annunciation when at least one of the determined linear distortion error and the non-linear distortion error is greater than or equal to the corresponding registration error threshold, and outputting a second annunciation, different from the first annunciation, when the determined linear distortion error and the determined non-linear distortion error are less than the corresponding registration error. ### Claim 3 (depends on 1) The method of claim 1, further comprising mounting at least one optically transparent blank slide within the sample handling apparatus, wherein the at least one blank slide is adjacent to the self-test slide when data is acquired. ### Claim 4 (depends on 1) The method of claim 1, wherein the array of first features is arranged in a rectangular shape. ### Claim 5 (depends on 1) The method of claim 1, wherein a center-center spacing between nearest neighbor first features is approximately equal. ### Claim 6 (depends on 1) The method of claim 1, wherein the array of first features has a minimum linear density of four pixels. ### Claim 7 (depends on 1) The method of claim 1, wherein the first features are dots and the at least one second feature is a square. ### Claim 8 (depends on 7) The method of claim 7, wherein a diameter of the dots is less than a side length of the square. ### Claim 9 (depends on 1) The method of claim 1, wherein the at least one second feature is positioned adjacent to a corner of the pattern. ### Claim 10 (depends on 1) The method of claim 1, wherein the at least one second feature is four second features, each second feature being positioned adjacent to a corner of the pattern. ### Claim 11 (depends on 1) The method of claim 1, wherein the first features are not lines. ### Claim 12 (depends on 1) The method of claim 1, wherein the pattern is a first pattern and a second pattern spaced apart from one another, wherein the array of first features of the first pattern and the second pattern are approximately the same and wherein an angle of rotation of the at least one second feature of the first pattern and the second pattern are different. ### Claim 13 (depends on 12) The method of claim 12, wherein the sample handling apparatus comprises a first image sensor and a second image sensor, wherein the first image sensor acquires first data representing a single image of the first pattern, and wherein the second image sensor acquires second data representing a single image of the second pattern. ### Claim 14 (depends on 1) The method of claim 1, wherein determining the linear distortion error comprises: detecting the array of first features of the pattern; registering the detected array of first features with an ideal array of first features using a two-dimensional similarity transformation; and estimating the linear distortion error from a registration error extracted from the registered array of first features. ### Claim 15 (depends on 1) The method of claim 1, wherein determining the non-linear distortion error comprises: detecting the array of first features of the pattern; registering the detected array of first features with an ideal array of first features using a homography transformation; and estimating the non-linear distortion error from a registration error extracted from the registered array of first features. ### Claim 16 (depends on 1) The method of claim 1, further comprising: detecting, by the data processor, features within one or more predetermined regions of the single image of the pattern; applying, by the data processor, a similarity transformation to the single image of the pattern to generate transformed test pattern features; determining, by the data processor, a transformation error between the transformed test pattern features and transformed ideal test pattern features; comparing, by the data processor, a first similarity transformation error to a second similarity transformation error; outputting, by the data processor, the first annunciation when the first similarity transformation error is greater than or equal to a similarity transformation error threshold; and outputting, by the data processor, the second annunciation when the first similarity transformation error is less than the similarity transformation error threshold. ### Claim 17 (depends on 1) The method of claim 1, further comprising: displaying, within a user interface of the sample handling apparatus, the single image of the pattern and a query prompting a user to provide input regarding whether or not an entire pattern is visible therein; receiving, by the data processor via the user interface, a user input in response to the displayed query; outputting, by the data processor, the first annunciation when the user input is a negative reply; and outputting, by the data processor, the second annunciation when the user input is a positive reply. ### Claim 18 (depends on 1) The method of claim 1, further comprising: determining, by the data processor from a single test image pattern data, a first illumination at a selected edge of the acquired image and a second illumination at a center of the acquired image; determining, by the data processor, an illumination difference between the first and second illumination; comparing, by the data processor, the illumination difference to an illumination difference threshold; outputting, by the data processor, the first annunciation when the illumination difference is greater than or equal to the illumination difference threshold; and outputting, by the data processor, the second annunciation when the illumination difference is less than the illumination difference threshold.