Methods and Systems for Image Data Processing

• US 20070064990A1
• Filed: 09/21/2006
• Published: 03/22/2007
• Est. Priority Date: 09/21/2005
• Status: Active Grant

• Current Assignee: Luminex Corporation (DiaSorin S.p.A.)
• Original Assignee: Luminex Corporation (DiaSorin S.p.A.)
• Inventors: Roth, Wayne
• Granted Patent: US 8,031,918 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: G01N 15/1433 using image recognition
• CPC Class Codes: G01N 15/1456 without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals
• CPC Class Codes: G06T 2207/10064 Fluorescence image
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/30024 Cell structures in vitro; Tissue sections in vitro
• CPC Class Codes: G06T 2207/30072 Microarray; Biochip, DNA array; Well plate
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation
• CPC Class Codes: G06V 20/695 Preprocessing, e.g. image segmentation

Abstract

Methods, storage mediums, and systems for image data processing are provided. Embodiments for the methods, storage mediums, and systems include configurations to perform one or more of the following steps: background signal measurement, particle identification using classification dye emission and cluster rejection, inter-image alignment, inter-image particle correlation, fluorescence integration of reporter emission, and image plane normalization.

Claims

1. A computer-implemented method, comprising:

separating an image of particles having fluorescence-material associated therewith into an array of subsections;

determining a statistical value of an optical parameter measured for a plurality of pixels within a subsection; and

assigning the determined statistical value as background signal for the corresponding subsection.

2. The computer-implemented method of claim 1, wherein the step of determining the statistical value of the optical parameter comprises determining the statistical value of the optical parameter among all of the pixels with the subsection.

3. The computer-implemented method of claim 2, further comprising determining the occupancy of particles within the image is less than a predetermined threshold prior to the step of determining the statistical value of the optical parameter.

4. The computer-implemented method of claim 2, further comprising determining the occupancy of particles within the image is less than approximately 50% prior to the step of determining the statistical value of the optical parameter.

5. The computer-implemented method of claim 1, further comprising identifying pixels within the subsection that exhibit an optical parameter value above a first predetermined threshold prior to the step of determining the statistical value of the optical parameter within the subsection, wherein the step of determining the statistical value of the optical parameter for a plurality of pixels within the subsection comprises determining the statistical value of the optical parameter solely among a set of pixels within the subsection which are not identified to exhibit an optical parameter value above the first predetermined threshold.

6. The computer-implemented method of claim 5, further comprising grouping the identified pixels with one or more pixels arranged immediately adjacent thereto prior to the step of determining the statistical value of the optical parameter, wherein the set of pixels used to determine the statistical value of the optical parameter exclude the grouped pixels.

7. The computer-implemented method of claim 5, further comprising determining the occupancy of particles within the image is greater than or equal to a second predetermined threshold prior to the step of determining the statistical value of the optical parameter.

8. The computer-implemented method of claim 5, further comprising determining the occupancy of particles within the image is greater than or equal to approximately 50% prior to the step of determining the statistical value of the optical parameter.

9. The computer-implemented method of claim 1, wherein the steps of determining a statistical value of the optical parameter and assigning the determined statistical value as background signal are conducted for each of a plurality of the subsections in the array, and wherein the method further comprises applying a two-dimensional statistical filter on the array of subsections subsequent to assigning the determined statistical values as background signal for each of the plurality of subsections.

10. The computer-implemented method of claim 1, wherein the step of determining the statistical value of the optical parameter comprises determining the median value of the optical parameter.

11. A storage medium comprising program instructions which are executable by a processor for:

analyzing an image of particles having fluorescence-material associated therewith to identify one or more pixels within the image that exhibit an optical parameter value above a first predetermined threshold;

determining locations within sets of the one or more identified pixels that respectively exhibit maximum values for the optical parameter within the sets; and

computing a rate of intensity change of the optical parameter for a plurality of pixels surrounding at least one of the locations.

12. The storage medium of claim 11, further comprising program instructions executable by a processor for:

accepting the plurality of pixels for further evaluation upon computing the rate of intensity change is greater than or equal to a second predetermined threshold; and

rejecting the plurality of pixels for further evaluation upon computing the rate of intensity change is less than the second predetermined threshold.

13. The storage medium of claim 11, wherein the program instructions for computing the rate of intensity change comprise program instructions for:

summing values of the optical parameter for a first set of the plurality of pixels arranged within a first predetermined radius surrounding the at least one location;

summing values of the optical parameter for a second set of the plurality of pixels arranged within a second predetermined radius surrounding the at least one location, wherein the second predetermined radius is distinct from the first predetermined radius;

determining a ratio of the summed values respectively computed for the first and second sets of pixels;

accepting the plurality of pixels for further evaluation upon determining the ratio differs from a set value by an amount less than or equal to a second predetermined threshold; and

rejecting the plurality of pixels for further evaluation upon determining the ratio differs from the set value by an amount greater than the second predetermined threshold.

14. The storage medium of claim 13, wherein the first predetermined radius is approximately equal to a projected diameter of a single particle within the image, wherein the projected diameter is based on the component configurations of a system used to image the particles.

15. The storage medium of claim 13, wherein the second predetermined radius is approximately 1.5 times greater than a projected diameter of a single particle within the image, wherein the projected diameter is based on the component configurations of a system used to image the particles.

16. The storage medium of claim 11, wherein the program instructions for determining the locations comprise program instructions for ascertaining peak pixels among the sets of one or more identified pixels that respectively exhibit maximum values for the optical parameter.

17. The storage medium of claim 16, wherein the program instructions for determining the locations further comprise program instructions for computing a centroid location within at least one of the sets of one or more identified pixels based upon the values of the optical parameter within the peak pixel corresponding to the at least one set and within pixels neighboring the peak pixel contained by a second predetermined radius surrounding the peak pixel.

18. The storage medium of claim 17, wherein the program instructions for determining the location further comprise program instructions for assigning the centroid location as the location exhibiting the maximum value for the optical parameter within the at least one set upon determining a dimension of the centroid location is greater than approximately 50% of a pixel width within the image.

19. The storage medium of claim 16, further comprising program instructions for:

computing a distance between two of the peak pixels; and

rejecting for further evaluation a set of pixels corresponding to one of the two peak pixels upon computing the distance is less than a second predetermined threshold.

20. A system configured to acquire and process image data, comprising:

an imaging subsystem configured to;

image, at different wavelength bands, particles disposed within the imaging subsystem; and

acquire data corresponding to emissions of imaged particles; and

a storage medium comprising program instructions which are executable by a processor for;

storing data acquired for multiple images of the particles, wherein each of the multiple images corresponds to a different wavelength band;

creating a composite image of the multiple images; and

manipulating the coordinates of at least one of the multiple images such that spots corresponding to the particles within each of the multiple images converge within an ensuing composite image.

21. The system of claim 20, wherein the program instructions for manipulating the coordinate parameters comprise program instructions for performing at least one of an orthogonal offset of the coordinates and rotation of the at least one of the multiple image.

22. The system of claim 20, wherein the program instructions for manipulating the coordinate parameters comprise program instructions for:

algorithmically determining an offset to modify coordinates of at least one of the multiple images such that an amount of color variance among the spots in an ensuing composite image is reduced relative to a preceding composite image;

adjusting the coordinates of the at least one image by the predetermined offset; and

creating a different composite image of the multiple images subsequent to the step of adjusting the coordinates of the at least one image.

23. The system of claim 22, wherein the program instructions for manipulating the coordinate parameters further comprise program instructions for:

determining the color variance among spots in the different composite image; and

iterating the steps of algorithmically determining an offset, adjusting the coordinates of the at least one image, creating a different composite image, and determining the color variance among spots until the amount of color variance among the spots of a composite image is less than a predetermined error allowance for the algorithmically determined offset.

24. The system of claim 20, wherein the program instructions for manipulating the coordinate parameters comprise program instructions for:

adjusting coordinates of at least one image by a predetermined offset;

creating a different composite image of the multiple images subsequent to the step of adjusting the coordinates of the at least one image;

computing an aggregate error or mean squared difference of intensities among pixels corresponding to spots within the different composite image;

repeating the steps of adjusting the coordinates of the at least one image, creating a different composite image, and computing the aggregate error or mean squared difference of intensities with different predetermined offsets for a predetermined number of iterations;

comparing the computed values of aggregate error or mean squared difference of intensities for each of the different composite images; and

saving offset values for each image having adjusted coordinates corresponding to the composite image having the smallest aggregate error or mean squared difference of intensities.

25. The system of claim 20, wherein the program instructions for manipulating the coordinate parameters comprise program instructions for:

adjusting coordinates of at least one image by a predetermined offset;

creating a different composite image of the multiple images subsequent to the step of adjusting the coordinates of the at least one image;

computing an aggregate error or mean squared difference among locations of spots within the different composite image;

repeating the steps of adjusting the coordinates of the at least one image, creating a different composite image, and computing the aggregate error or mean squared difference of spot locations with different predetermined offsets for a predetermined number of iterations;

comparing the computed values of aggregate error or mean squared difference of the spot locations for each of the different composite images; and

saving offset values for each image having adjusted coordinates corresponding to the composite image having the smallest aggregate error or mean squared difference of spot locations.

26. The system of claim 20, wherein the storage medium further comprises program instructions which are executable by a processor for:

determining whether a particle imaged at one wavelength band used to classify the particles disposed within the imaging subsystem is further imaged at a different wavelength band used to classify the particles;

accepting the particle for further evaluation upon determining the particle is imaged at the different wavelength band; and

rejecting the particle for further evaluation upon determining the particle is not imaged at the different wavelength band.

27. A computer-implemented method, comprising:

analyzing a first image of particles having a uniform concentration of fluorescence-material associated therewith to identify one or more pixels within the first image that exhibit an optical parameter value above a first predetermined threshold;

categorizing, within respective subsections of the first image, collections of pixels identified during the step of analyzing the first image;

developing for each respective subsection within the first image a statistic representative of the level of the optical parameter for the collections of pixels categorized thereto;

analyzing a second image of particles having an unknown concentration of fluorescence-material associated therewith to identify one or more pixels within the second image that exhibit an optical parameter value above the first predetermined threshold;

categorizing, within respective subsections of the second image, collections of pixels identified during the step of analyzing the second image, wherein dimensions of the subsections in the second image are substantially equal to the subsections in the first image; and

dividing the optical parameter value for each of the pixels identified during the step of analyzing the second image by the statistic developed for the corresponding first image subsection to obtain a normalized value for the optical parameter.

28. The computer-implemented method of claim 27, further comprising:

analyzing a third image of the particles having the uniform concentration of fluorescence-material associated therewith to identify one or more pixels within the third image that exhibit an optical parameter value above the first predetermined threshold, wherein the third image is formed using an illumination source of a different wavelength than the first image;

categorizing, within respective subsections of the third image, collections of pixels identified during the step of analyzing the third image, wherein dimensions of the subsections in the third image are substantially equal to the subsections in the first image;

developing for each respective subsection within the third image a statistic representative of the level of the optical parameter for the collections of pixels categorized thereto; and

saving the statistics developed for each respective subsection of the first and third images in matrices specific to the wavelengths used to form the first and third images.

29. The computer-implemented method of claim 27, further comprising:

prior to the step of analyzing the second image, analyzing a third image of a different set of particles having a uniform concentration of fluorescence-material associated therewith to identify one or more pixels within the third image that exhibit an optical parameter value above the first predetermined threshold;

categorizing, within respective subsections of the third image, collections of pixels identified during the step of analyzing the third image, wherein dimensions of the subsections in the second image are substantially equal to the subsections in the first image;

developing for each respective subsection of the third image a statistic representative of the level of the optical parameter for the collections of pixels classified thereto; and

computing a mean of the statistics developed for each respective subsections of the first and third images.

30. The computer-implemented method of claim 29, further comprising:

computing a statistical value which is representative of all of the statistics developed for the respective subsections; and

dividing a predetermined numerical value associated with a level of the optical parameter associated with the different sets of particles having uniform concentrations of fluorescence-material associated therewith by the computed statistical value to compute a calibrator value.

31. The computer-implemented method of claim 30, further comprising multiplying the normalized value by the calibrator value.