Methods and devices for reading microarrays
US-10303922-B2 · May 28, 2019 · US
US10586095B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10586095-B2 |
| Application number | US-201916374739-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 3, 2019 |
| Priority date | May 22, 2009 |
| Publication date | Mar 10, 2020 |
| Grant date | Mar 10, 2020 |
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In one embodiment of the invention, a method to image a probe array is described that includes focusing on a plurality of fiducials on a surface of an array. The method utilizes obtaining the best z position of the fiducials and using a surface fitting algorithm to produce a surface fit profile. One or more surface non-flatness parameters can be adjusted to improve the flatness image of the array surface to be imaged.
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What is claimed is: 1. A method for improving image flatness of a surface image of a probe array, the method comprising: providing a probe array and one or more fiducials, said probe array comprising a plurality of sub-arrays; imaging the one or more fiducials at one or more of positions; determining a position measurement for each of the one or more fiducials; generating a surface fit profile based on a plurality of the position measurements; and imaging a sub-array and adjusting one or more surface non-flatness parameters based on the surface fit profile to improve the image flatness of the surface image of the sub-array. 2. The method of claim 1 , wherein the position measurement of each fiducial is determined based on image sharpness. 3. The method of claim 1 , wherein determining the position measurement comprises determining a best position measurement for each of the fiducials at which the imaging is sharpest. 4. The method of claim 1 , wherein determining the position measurement comprises using quadratic interpolation for at least one of the fiducials. 5. The method of claim 1 , wherein the surface fit profile is generated using a surface-fitting algorithm. 6. The method of claim 5 , wherein the surface-fitting algorithm comprises at least one of a least square algorithm, a sub-plane surface fit algorithm, and a B spline surface fit. 7. The method of claim 1 , wherein the one or more surface non-flatness parameters comprise a sub-array tilt angle. 8. The method of claim 1 , wherein adjusting the one or more surface non-flatness parameters comprises adjusting a position of a stage on which the probe array is mounted. 9. The method of claim 8 , wherein the stage is a two-axis tilt stage. 10. The method of claim 8 , wherein the stage is a three-axis translation stage. 11. The method of claim 1 , wherein the one or more surface non-flatness parameters comprise an optical parameter. 12. The method of claim 1 , wherein the one or more surface non-flatness parameters comprise a focal plane position. 13. The method of claim 1 , wherein the fiducials comprise at least 4, 5, 9, 12 or 15 fiducials. 14. The method of claim 1 , wherein the one or more fiducials are imaged at one or more positions along an axis of translation. 15. The method of claim 14 , wherein the axis of translation is substantially perpendicular to a plane of the probe array. 16. The method of claim 1 , wherein imaging the one or more fiducials comprises adjusting a position of a stage on which the probe array is mounted. 17. The method of claim 1 , wherein the probe array is a DNA array. 18. The method of claim 1 , wherein the probe array is a peptide array. 19. The method of claim 1 , wherein the one or more fiducials are on the probe array. 20. The method of claim 1 , wherein the one or more fiducials are of a corner sub-array of the probe array.
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