Adaptive background detection and signal quantification systems and methods

• US 10,395,350 B2
• Filed: 02/26/2018
• Issued: 08/27/2019
• Est. Priority Date: 07/26/2013
• Status: Expired due to Fees

• Current Assignee: Li-Cor Biotech LLC
• Original Assignee: Li & S Company Limited (Yesco Holdings Co., Ltd.)
• Inventors: Humphrey, Patrick G.
• Primary Examiner(s): Caschera, Antonio A
• Application Number:
  US15/905,416
• Publication Number:
  US 20180182080A1
• Time in Patent Office: 547 Days
• CPC Class Codes: G06T 2207/20024 Filtering details
• CPC Class Codes: G06T 2207/20028 Bilateral filtering
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 2207/20208 High dynamic range [HDR] image processing
• CPC Class Codes: G06T 5/40 using histogram techniques
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 5/90 Dynamic range modification of images or parts thereof
• CPC Class Codes: G06T 5/94 based on local image properties, e.g. for local contrast enhancement
• CPC Class Codes: G09G 2320/0271 Adjustment of the gradation levels within the range of the gradation scale, e.g. by redistribution or clipping
• CPC Class Codes: G09G 2320/029 by monitoring one or more pixels in the display panel, e.g. by monitoring a fixed reference pixel
• CPC Class Codes: G09G 2320/066 for control of contrast
• CPC Class Codes: G09G 2320/0673 for control of gamma adjustment, e.g. selecting another gamma curve
• CPC Class Codes: G09G 2320/08 Arrangements within a display terminal for setting, manually or automatically, display parameters of the display terminal
• CPC Class Codes: G09G 2360/16 Calculation or use of calculated indices related to luminance levels in display data
• CPC Class Codes: G09G 5/10 Intensity circuits

Abstract

Systems and method for processing image data of an image to determine a signal quantification value for a signal of interest in the image data. The method includes identifying a first region of the image including a plurality of pixels, each pixel having a pixel intensity value, said first region including the signal of interest and a background signal component; determining, using the image data, a total number of discrete pixel intensity values for the plurality of pixels in the first region; calculating, for each discrete pixel intensity value, a total number of the pixels in the first region having that discrete pixel intensity value; determining a mean value of the background signal component based on the total number of pixels for each discrete pixel intensity value; and calculating a signal quantification value, for the signal of interest, that represents the signal of interest with the background signal component removed.

Claims

1. A processor-implemented method of processing image data of an image to determine a signal quantification value for a signal of interest in the image data, the method comprising:

identifying a first region of the image, the first region including a plurality of pixels, each pixel having a pixel intensity value, said first region including the signal of interest and a background signal component;

determining, using the image data, a total number of discrete pixel intensity values for the plurality of pixels in the first region;

calculating, for each discrete pixel intensity value, a total number of the pixels in the first region having that discrete pixel intensity value;

determining a mean value of the background signal component based on the total number of pixels for each discrete pixel intensity value;

validating a distribution of the background signal component in the first region;

calculating a signal quantification value for the signal of interest, wherein the signal quantification value represents the signal of interest with the background signal component removed; and

displaying the signal quantification value on an output device.

2. The method of claim 1, the identifying a first region of an image is performed automatically.

3. The method of claim 1, the identifying a first region of an image is performed responsive to user input identifying the first region in the image.

4. The method of claim 1, wherein the determining a mean value of the background signal component includes:

generating an initial histogram of the number of discrete pixel intensity values for the first region;

determining a background portion of the initial histogram; and

thereafter

determining the mean value of the background signal component based on a parameter of the background portion of the initial histogram.

5. The method of claim 1, wherein the calculating a signal quantification value for the signal of interest includes applying the formula Signal Quantification Value =Σ

(ROI)−

M·

μ

, wherein Σ

(ROI) represents a summation of the pixel intensity values for the first region, wherein M represents the total number of discrete pixel intensity values and μ

represents the mean value of the background signal component.

6. The method of claim 1, wherein the identifying a first region of an image includes deriving the first region of the image based on an initial region of the image.

7. The method of claim 6, wherein the deriving includes expanding a boundary of the initial region along at least one direction to form a derived region.

8. The method of claim 7, wherein the calculating a signal quantification value for the signal of interest includes applying the formula Signal Quantification Value =Σ

(ROI1)−

M1 ·

μ

2, wherein Σ

(ROI1) represents a summation of the pixel intensity values for the initial region, wherein M1 represents the total number of discrete pixel intensity values for the initial region and μ

2 represents the mean value of the background signal component for the derived region.

9. The method of claim 1, further including providing the signal quantification value as an output to a device other than the output device.

10. The method of claim 1, wherein the validating includes:

generating a background intensity histogram of pixel intensity values for the first region, the first region having a border defined by two orthogonal axes;

generating a first pixel location histogram corresponding to a first axis of the two orthogonal axes, wherein the first pixel location histogram identifies a number of pixels in the background intensity histogram at pixel locations along the first axis;

generating a second pixel location histogram corresponding to a second axis of the two orthogonal axes, wherein the second pixel location histogram identifies a number of pixels in the background intensity histogram at pixel locations along the second axis; and

determining a uniformity of each of the first pixel location histogram and the second pixel location histogram.

11. The method of claim 10, wherein if either or both of the first pixel location histogram and the second pixel location histogram are determined to be non-uniform, the method further comprises:

adjusting a dimension of the first region along one or both of the first axis and the second axis based on the determined non-uniformity to form an adjusted region; and

repeating the steps of generating a background intensity histogram, generating a first pixel location histogram and generating a second pixel location histogram and determining a uniformity using the adjusted region as the first region in the step of generating the background intensity histogram.

12. A processor-implemented method of processing image data of an image to determine a signal quantification value for a signal of interest in the image data, the method comprising:

identifying a first region of the image, the first region including a plurality of pixels, each pixel having a pixel intensity value, said first region including the signal of interest and a background signal component;

determining, using the image data, a total number of discrete pixel intensity values for the plurality of pixels in the first region;

calculating, for each discrete pixel intensity value, a total number of the pixels in the first region having that discrete pixel intensity value;

determining a mean value of the background signal component based on the total number of pixels for each discrete pixel intensity value, wherein the determining a mean value of the background signal component includes;

generating an initial histogram of the number of discrete pixel intensity values for the first region;

determining a background portion of the initial histogram; and

thereafter

determining the mean value of the background signal component based on a parameter of the background portion of the initial histogram;

calculating a signal quantification value for the signal of interest, wherein the signal quantification value represents the signal of interest with the background signal component removed; and

displaying the signal quantification value on an output device, wherein the initial histogram includes a plurality of bins, and wherein the determining a background portion of the initial histogram includes iteratively repeating, one or more times;

a) identifying a first bin as a bin having a greatest count of pixel intensity values;

b) identifying a left bin as a closest bin to the left of the first bin in the initial histogram that has a count that is less than a first count percentage of the greatest count;

c) identifying a right bin as a closest bin to the right of the first bin in the initial histogram that has a count that is less than a second count percentage of the greatest count; and

d) generating an updated histogram of pixel intensity values having a range between the identified left bin and identified right bin, wherein the updated histogram includes the background portion of the initial histogram,

wherein for each successive iteration the updated histogram is used as the initial histogram.

13. The method of claim 12, wherein the determining the mean value of the background signal component includes fitting a Gaussian curve to the updated histogram, wherein the mean value is based on a parameter of the fitted Gaussian curve.

14. The method of claim 12, wherein the determining the mean value of the background signal component includes:

calculating a mean intensity value of the updated histogram.

15. The method of claim 14, further including determining a standard deviation of the mean intensity value.

16. The method of claim 13, wherein the validating a distribution of the background signal component in the first region includes:

generating a final updated histogram of pixel intensity values for the first region, the first region having a border defined by two orthogonal axes;

generating a first pixel location histogram corresponding to a first axis of the two orthogonal axes, wherein the first pixel location histogram identifies a number of pixels in the final updated histogram at pixel locations along the first axis;

generating a second pixel location histogram corresponding to a second axis of the two orthogonal axes, wherein the second pixel location histogram identifies a number of pixels in the final updated histogram at pixel locations along the second axis; and

determining a uniformity of each of the first pixel location histogram and the second pixel location histogram.

17. The method of claim 16, wherein if either or both of the first pixel location histogram and the second pixel location histogram are determined to be non-uniform, the method further comprises:

adjusting a dimension of the first region along one or both of the first axis and the second axis based on the determined non-uniformity to form an adjusted region; and

repeating, using the adjusted region as the first region, the steps of determining a total number of discrete pixel intensity values, calculating, for each discrete pixel intensity value, a total number of the pixels in the region having that discrete intensity value and determining a mean value of the background signal component using the adjusted image; and

repeating the step of validating a distribution of the background signal component in the first region using the adjusted region as the first region.

18. A processor-implemented method of processing image data of an image to determine a signal quantification value for a signal of interest in the image data, the method comprising:

identifying a first region of the image the first region including a plurality of pixels each pixel having a pixel intensity value, said first region including the signal of interest and a background signal component;

determining, using the image data, a total number of discrete pixel intensity values for the plurality of pixels in the first region;

calculating, for each discrete pixel intensity value, a total number of the pixels in the first region having that discrete pixel intensity value;

determining a mean value of the background signal component based on the total number of pixels for each discrete pixel intensity value;

calculating a signal quantification value for the signal of interest, wherein the signal quantification value represents the signal of interest with the background signal component removed; and

displaying the signal quantification value on an output device, wherein the image includes a western blot image, and wherein the signal of interest is a protein signal in a signal lane of the western blot image, and wherein the first region includes a portion of the signal lane.

19. The method of claim 18, A further including validating a distribution of the background signal component in the first region.

20. A non-transitory computer readable medium storing code, which when executed by one or more processors cause the one or more processors to implement a method of processing image data of an image to determine a signal quantification value for a signal of interest in the image data, the code including instructions to:

receive the image data;

identify a first region of the image, the first region including a plurality of pixels, each pixel having a pixel intensity value, said first region including the signal of interest and a background signal component;

determine, using the image data, a total number of discrete pixel intensity values for the plurality of pixels in the first region;

calculate, for each discrete pixel intensity value, a total number of the pixels in the first region having that discrete pixel intensity value;

determine a mean value of the background signal component based on the total number of pixels for each discrete pixel intensity value;

validate a distribution of the background signal component in the first region;

calculate a signal quantification value for the signal of interest, wherein the signal quantification value represents the signal of interest with the background signal component removed; and

display the signal quantification value on a display communicatively coupled with the one or more processors.

21. An image processing system, comprising:

a processor coupled to a memory storing instructions, and a display, wherein the instructions, when executed by the processor cause the processor to;

receive image data of an image;

determine a signal quantification value for a signal of interest in the image data by;

identifying a first region of the image, the first region including a plurality of pixels, each pixel having a pixel intensity value, said first region including the signal of interest and a background signal component;

determining, using the image data, a total number of discrete pixel intensity values for the plurality of pixels in the first region;

calculating, for each discrete pixel intensity value, a total number of the pixels in the first region having that discrete pixel intensity value;

determining a mean value of the background signal component based on the total number of pixels for each discrete pixel intensity value;

validating a distribution of the background signal component in the first region and

calculating a signal quantification value for the signal of interest, wherein the signal quantification value represents the signal of interest with the background signal component removed; and

display the signal quantification value for the signal of interest on the display.

22. The image processing system of claim 21, wherein the instructions for validating the distribution of the background signal component in the first region further cause the processor to:

generate a background intensity histogram of pixel intensity values for the first region, the first region having a border defined by two orthogonal axes;

generate a first pixel location histogram corresponding to a first axis of the two orthogonal axes, wherein the first pixel location histogram identifies a number of pixels in the background intensity histogram at pixel locations along the first axis;

generate a second pixel location histogram corresponding to a second axis of the two orthogonal axes, wherein the second pixel location histogram identifies a number of pixels in the background intensity histogram at pixel locations along the second axis; and

determine a uniformity of each of the first pixel location histogram and the second pixel location histogram.

23. The image processing system of claim 22, wherein if either or both of the first pixel location histogram and the second pixel location histogram are determined to be non-uniform, the instructions further cause the processor to:

adjust a dimension of the first region along one or both of the first axis and the second axis based on the determined non-uniformity to form an adjusted region; and

repeat said instructions to generate a background intensity histogram, generate a first pixel location histogram and generate a second pixel location histogram and determine a uniformity using the adjusted region as the first region when generating the background intensity histogram.