Image analysis useful for patterned objects

Patent metadata

Field	Value
Publication number	US-11308640-B2
Application number	US-201916706092-A
Country	US
Kind code	B2
Filing date	Dec 6, 2019
Priority date	Nov 1, 2013
Publication date	Apr 19, 2022
Grant date	Apr 19, 2022

Abstract

A method of registering features in a repeating pattern can include (a) providing an object having a repeating pattern of features and a fiducial; (b) obtaining a target image of the object, wherein the target image includes the repeating pattern of features and the fiducial; (c) comparing the fiducial in the target image to reference data, wherein the reference data includes xy coordinates for a virtual fiducial; and (d) determining locations for the features in the target image based on the comparison of the virtual fiducial in the reference data to the fiducial in the data from the target image. The fiducial can have at least concentric circles that produce three different signal levels. The locations of the features can be determined at a variance of less than 5 μm.

First claim

What is claimed is:

1. A system, comprising:
a detection device configured to obtain a target image of an object;
a storage device storing a program for image analysis;
a processor coupled to the detection device and configured to execute the program for image analysis to:
obtain the target image of the object from the detection device, wherein the target image comprises a repeating pattern of features in an xy plane and a fiducial, the features and fiducial being detectable in the target image, wherein the fiducial comprises at least 3 concentric circles;
load, from reference data, xy coordinates for a virtual fiducial, wherein the virtual fiducial comprises a point of reference that is derived from a source other than the object or target image and wherein the virtual fiducial simulates predefined signal levels and xy coordinates for the at least 3 concentric circles, wherein the predefined signal levels comprise at least 3 different predefined signal levels;
compute a cross-correlation between the virtual fiducial and the fiducial detectable in the target image to determine an offset between the virtual fiducial in the reference data and the fiducial in the data from the target image; and
transform locations for the features in the target image based on the cross correlation.

2. The system of claim 1 , wherein the at least 3 different predefined signal levels are signal intensity levels.

3. The system of claim 1 , wherein the cross-correlation comprises an alignment of the 3 different predefined signal levels with corresponding different signal intensities in the fiducial of the target image.

4. The system of claim 1 , wherein the reference data further comprises signal intensity, brightness, and/or color for virtual fiducial.

5. The system of claim 1 , wherein the reference data further comprises a correction factor that adjusts the fiducial or the virtual fiducial for distortions of the detection device.

6. The system of claim 1 , wherein the processor is further configured to assign a nucleotide identity to a transformed location in the target image.

7. The system of claim 1 , wherein the detection device comprises a scanning detector.

8. A computer-implemented method for registering features in repeating patterns, comprising:
obtaining a target image of an object using a detection apparatus, wherein the target image comprises a repeating pattern of features in an xy plane of the object and a fiducial, the features and fiducial being detectable in the target image, wherein the fiducial comprises at least 3 concentric circles;
loading, from reference data, xy coordinates for a virtual fiducial, wherein the virtual fiducial comprises a point of reference that is derived from a source other than the object or target image and wherein the virtual fiducial simulates predefined signal levels and xy coordinates for the at least 3 concentric circles, wherein the predefined signal levels comprise at least 3 different predefined signal levels;
computing a cross-correlation between the virtual fiducial and the fiducial detectable in the target image to determine an offset between the virtual fiducial in the reference data and the fiducial in the data from the target image; and
transforming locations for the features in the target image based on the cross correlation.

9. The method of claim 8 , wherein the at least 3 different predefined signal levels are signal intensity levels.

10. The method of claim 8 , wherein the cross-correlation comprises an alignment of the 3 different predefined signal levels with corresponding different signal intensities in the fiducial of the target image.

11. The method of claim 8 , wherein the reference data further comprises signal intensity, brightness, and/or color for virtual fiducial.

12. The method of claim 8 , wherein the reference data further comprises a correction factor that adjusts the fiducial or the virtual fiducial for distortions of the detection device.

13. The method of claim 8 , wherein the processor is further configured to assign a nucleotide identity to a transformed location in the target image.

14. The method of claim 8 , wherein the detection device comprises a scanning detector.

15. One or more tangible, computer-readable media, comprising processor-executable instructions that when executed cause a processor to perform acts comprising:
obtaining a target image of an object using a detection apparatus, wherein the target image comprises a repeating pattern of features in an xy plane of the object and a fiducial, the features and fiducial being detectable in the target image, wherein the fiducial comprises at least 3 concentric circles;
loading, from reference data, xy coordinates for a virtual fiducial, wherein the virtual fiducial comprises a point of reference that is derived from a source other than the object or target image and wherein the virtual fiducial simulates predefined signal levels and xy coordinates for the at least 3 concentric circles, wherein the predefined signal levels comprise at least 3 different predefined signal levels;
computing a cross-correlation between the virtual fiducial and the fiducial detectable in the target image to determine an offset between the virtual fiducial in the reference data and the fiducial in the data from the target image; and
transforming locations for the features in the target image based on the cross correlation.

16. The one or more tangible, computer-readable media of claim 15 , wherein the at least 3 different predefined signal levels are signal intensity levels.

17. The one or more tangible, computer-readable media of claim 15 , wherein the cross-correlation comprises an alignment of the 3 different predefined signal levels with corresponding different signal intensities in the fiducial of the target image.

18. The one or more tangible, computer-readable media of claim 15 , wherein the reference data further comprises signal intensity, brightness, and/or color for virtual fiducial.

19. The one or more tangible, computer-readable media of claim 15 , wherein the reference data further comprises a correction factor that adjusts the fiducial or the virtual fiducial for distortions of the detection device.

20. The one or more tangible, computer-readable media of claim 15 , wherein the processor is further configured to assign a nucleotide identity to a transformed location in the target image.

Assignees

• Illumina Inc

Inventors

• Vieceli John S
• Tanner Stephen
• Moon John A
• Bowen M Shane

Classifications

• G06T7/74 Primary

  involving reference images or patches · CPC title

• G06T2207/30024

  Cell structures in vitro; Tissue sections in vitro · CPC title

• G06T2207/30204

  Marker · CPC title