Automated detection and repositioning of micro-objects in microfluidic devices

Patent metadata

Field	Value
Publication number	US-2021090252-A1
Application number	US-202017062907-A
Country	US
Kind code	A1
Filing date	Oct 5, 2020
Priority date	Dec 9, 2014
Publication date	Mar 25, 2021
Grant date	—

Abstract

Methods are provided for the automated detection of micro-objects in a microfluidic device. In addition, methods are provided for repositioning micro-objects in a microfluidic device. In addition, methods are provided for separating micro-objects in a spatial region of the microfluidic device.

First claim

What is claimed:

1 . A method for the automated detection of micro-objects disposed within a microfluidic device, the method comprising:
capturing a first image of a region in the microfluidic device that may contain a micro-object of interest; inducing movement of fluid within said region; capturing a second image of said region; generating a differential image from the first and second images; and identifying a micro-object of interest based on the differential image.

2 . The method of claim 1 , wherein the region comprises one or more microfluidic device features that are captured in the first and second image, and wherein the differential image does not contain the one or more microfluidic device features.

3 . The method of claim 2 , wherein the one or more microfluidic device features include an array of phototransistors.

4 . The method of any one of claims 1 to 3 , wherein said first and second images are captured using a digital camera or a CCD device.

5 . The method of any one of claims 1 to 4 , wherein inducing movement of said fluid comprises introducing a discrete volume of fluid into said microfluidic device.

6 . The method of claim 5 , wherein said discrete volume of fluid is about 25 pL to about 100 pL.

7 . The method of any one of claims 1 to 6 , wherein said differential image is generated by subtracting said first image from said second image, or vice versa.

8 . The method of claim 7 , further comprising:
determining a first set of light intensity values for one or more pixels corresponding to the first image and a second set of light intensity value for one or more pixels corresponding to the second image; and subtracting the first set of light intensity values from the second set of light intensity values, or vice versa, to generate a set of positive-value pixels and a set of negative-value pixels.

9 . The method of claim 8 , further comprising:
analyzing the set of positive-value pixels to identify one or more sets of pixel clusters, wherein each pixel cluster comprises one or more pixels; determining, for each of the one or more sets of pixel clusters, a feature set comprising information representing one or more of: an area of the set of pixel clusters, a circumference of the set of pixel clusters, a global morphology of the set of pixel cluster, a local morphology of the set of pixel clusters, and a light intensity value associated with the set of pixel clustesr; and identifying, for each of the one or more sets of pixel clusters, whether the set of pixel clusters corresponds to a micro-object of interest, wherein the identification is based on the determined feature set for the set of pixel clusters.

10 . The method of claim 8 or 9 , further comprising:
detecting pairs of positive-value and negative-value pixels or pixel clusters that differ in their relative position by an amount consistent with said movement of fluid induced in said region; and
identifying each such pair as representing a current and former location, respectively, of the micro-object of interest.

11 . A method for the automated detection of micro-objects disposed within a microfluidic device, the method comprising:
capturing with an imaging device a first image of a region of a microfluidic device that may contain a micro-object of interest; shifting said microfluidic device relative to said imaging device; capturing with said imaging device a second image of the region, wherein said second image is shifted relative to said first image; aligning said first image with said second image; generating a differential image from said first and second images; and identifying a micro-object of interest based on the differential image.

12 . The method of claim 11 , wherein the region comprises one or more microfluidic device features that are captured in the first and second image, and wherein the differential image does not contain the one or more microfluidic device features.

13 . The method of claim 12 , wherein the one or more microfluidic device features include an array of phototransistors.

14 . The method of any one of claims 11 to 13 , wherein said imaging device is a digital camera or a CCD device.

15 . The method of any one of claims 11 to 14 , wherein shifting said microfluidic device comprises moving a stage that is holding said microfluidic device in a direction perpendicular to an optical axis of said imaging device.

16 . The method of any one of claims 11 to 15 , wherein said microfluidic device is shifted by about 2 to about 3 microns.

17 . The method of any one of claims 11 to 16 , wherein said first and second images are aligned computationally, and wherein regions of said first and second images that can't be aligned are discarded.

18 . The method of any one of claims 11 to 17 , wherein aligning said first and second images comprises aligning circuit elements within the microfluidic device.

19 . The method of any one of claims 11 to 18 , wherein generating said differential image comprises subtracting said first image from said second image, or vice versa.

20 . The method of claim 19 further comprising:
determining a first set of light intensity values for one or more pixels corresponding to the first image and a second set of light intensity value for one or more pixels corresponding to the second image; and
subtracting the first set of light intensity values from the second set of light intensity values, or vice versa, to generate a set of positive-value pixels and a set of negative-value pixels.

21 . The method of claim 20 , further comprising:
analyzing the set of positive-value pixels to identify one or more sets of pixel clusters, wherein each pixel cluster comprises one or more pixels; determining, for each set of pixel clusters of the one or more sets of pixel clusters, a feature set comprising information representing one or more of: an area of the set of pixel clusters, a circumference of the set of pixel clusters, a global morphology of the set of pixel clusters, a local morphology of the set of pixel clusters, and a light intensity value associated with the set of pixel clusters; and identifying, for each of the one or more sets of pixel clusters, whether the set of pixel clusters corresponds to a micro-object of interest, wherein the identification is based on the feature set determined for the set of pixel clusters.

22 . The method of claim 20 or 21 , further comprising:
detecting pairs of positive-value and negative-value pixels or pixel clusters that differ in their relative position by an amount consistent with said movement of said microfluidic device relative to said imaging device; and
identifying each such pair as representing a current and former location, respectively, of the micro-object of interest.

23 . A method for the automated detection of micro-objects disposed within a microfluidic device, the method comprising:
capturing an image of a region in the microfluidic device that may contain a micro-object of interest; determining periodic structures in the image using a Fourier transform; generating a filtered image by removing the period structures from the image; and identifying a micro-object of interest based on the filtered image.

24 . The method of claim 23 , wherein the periodic structures correspond to one or more microfluidic device features.

25 . The method of claim 24

Assignees

• Berkeley Lights Inc

Inventors

• Du Fenglei
• Lundquist Paul M
• Tenney John A
• Lionberger Troy A

Classifications

• B01L2400/0427

  Electrowetting · CPC title

• B01L2300/0645

  Electrodes · CPC title

• B01L3/50273 Primary

  characterised by the means or forces applied to move the fluids · CPC title

• G01N2015/1493

  Particle size · CPC title

• G01N15/1484

  microstructural devices · CPC title