WO2017019762A1 - Photométrie basée sur des images - Google Patents

Photométrie basée sur des images Download PDF

Info

Publication number
WO2017019762A1
WO2017019762A1 PCT/US2016/044245 US2016044245W WO2017019762A1 WO 2017019762 A1 WO2017019762 A1 WO 2017019762A1 US 2016044245 W US2016044245 W US 2016044245W WO 2017019762 A1 WO2017019762 A1 WO 2017019762A1
Authority
WO
WIPO (PCT)
Prior art keywords
sample
rgb
values
image
samples
Prior art date
Application number
PCT/US2016/044245
Other languages
English (en)
Inventor
Dionysios C. CHRISTODOULEAS
Alex Nemiroski
Ashok Ashwin Kumar
George M. Whitesides
Original Assignee
President And Fellows Of Harvard College
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by President And Fellows Of Harvard College filed Critical President And Fellows Of Harvard College
Publication of WO2017019762A1 publication Critical patent/WO2017019762A1/fr

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/02—Details
    • G01J3/0262—Constructional arrangements for removing stray light
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/02—Details
    • G01J3/0291—Housings; Spectrometer accessories; Spatial arrangement of elements, e.g. folded path arrangements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G01J3/2823—Imaging spectrometer
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G01J3/42—Absorption spectrometry; Double beam spectrometry; Flicker spectrometry; Reflection spectrometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters
    • G01J3/50—Measurement of colour; Colour measuring devices, e.g. colorimeters using electric radiation detectors
    • G01J3/51—Measurement of colour; Colour measuring devices, e.g. colorimeters using electric radiation detectors using colour filters
    • G01J3/513—Measurement of colour; Colour measuring devices, e.g. colorimeters using electric radiation detectors using colour filters having fixed filter-detector pairs
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/251—Colorimeters; Construction thereof
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/251—Colorimeters; Construction thereof
    • G01N21/253—Colorimeters; Construction thereof for batch operation, i.e. multisample apparatus
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G01J3/2803—Investigating the spectrum using photoelectric array detector
    • G01J2003/2813—2D-array
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/06—Illumination; Optics
    • G01N2201/064—Stray light conditioning

Definitions

  • Absorbance spectroscopy is the most common analytical technique used for chemical and biochemical analyses.
  • Test kits e.g., tube test kits and microtiter plate ELISA kits
  • important analytes e.g., metabolites, proteins, environmental pollutants
  • the cost-per-sample of these test kits is typically ⁇ $5.
  • spectrophotometers can cost from $2,000 to $50,000, depending on their specifications, versatility, and throughput.
  • approaches based on reflectance-mode imaging use custom software to spatially average the RGB values of all pixels of the image of each well, and then to calibrate the relationship between the average (mean) values of each well and concentration of the analyte, separately for each well.
  • An image based photometer includes a light source adapted to hold a well plate having multiple wells for testing samples, the light source providing a source of broadband white light for transmission through the multiple wells.
  • a sensing surface is positioned opposite the light source to receive light transmitted through the multiple wells and shield ambient light from transmission through the wells.
  • a method includes directing broadband white light through multiple samples to obtain transmitted light, obtaining multiple red, green, and blue (RGB) values for each sample, averaging the obtained multiple RGB values for each sample, and correlating the averaged values to provide an RGB- resolved absorbance of each sample to identify each sample.
  • RGB red, green, and blue
  • a processor readable storage device having instructions to cause a circuit based processor to perform operations including receiving an image of multiple samples based on broadband white light directed through the multiple samples, opening the image, selecting multiple red, green, and blue (RGB) pixels from the opened image for each sample, determining values for each of the RGB components of the pixels, averaging the obtained multiple RGB values for each sample, and correlating the averaged values to provide an RGB- resolved absorbance of each sample to identify each sample.
  • RGB red, green, and blue
  • FIG. 1 is a block perspective diagram of an image based photometer using a camera according to an example embodiment.
  • FIG. 2 is a perspective representation of an image based photometer utilizing a flatbed scanner based photometer according to an example embodiment.
  • FIG. 3 is a top view of a microtiter plate having multiple wells to hold samples for an image based photometer according to an example embodiment.
  • FIG. 4A is a histogram illustrating green channel pixel counts of a sample from a flatbed scanner photometer operating in transmittance mode according to an example embodiment.
  • FIG. 4B is a histogram illustrating green channel pixel counts of a sample from a flatbed scanner operating in reflectance mode.
  • FIG. 4C is a histogram illustrating green channel pixel counts of a sample from a CSI based flatbed scanner.
  • FIG. 4D is a table containing statistics corresponding to the counts of FIGs. 4 A, 4B, and 4C according to an example embodiment.
  • FIG 5 A is a histogram illustrating green channel pixel counts of a sample from a camera based photometer according to an example embodiment.
  • FIG. 5B is a histogram illustrating green channel pixel counts of a sample from a camera.
  • FIG. 5C is a table containing statistics corresponding to the counts of FIGs. 5 A and 5B according to an example embodiment.
  • FIG. 6A is a graph illustrating a flatbed scanner photometer light source intensity versus wavelength according to an example embodiment.
  • FIG. 6B is a graph illustrating sample transmittance versus wavelength using a flatbed scanner photometer according to an example embodiment.
  • FIG. 6C is a graph illustrating sensor sensitivity versus wavelength using a flatbed scanner photometer according to an example embodiment.
  • FIG. 6D is a graph illustrating captured light intensity versus wavelength using a flatbed scanner photometer according to an example embodiment.
  • FIG. 6E is a graph illustrating a camera photometer light source intensity versus wavelength according to an example embodiment.
  • FIG. 6F is a graph illustrating sample transmittance versus wavelength using a camera photometer according to an example embodiment.
  • FIG. 6G is a graph illustrating sensor sensitivity versus wavelength using a camera photometer according to an example embodiment.
  • FIG. 6H is a graph illustrating captured light intensity versus wavelength using a camera photometer according to an example embodiment.
  • FIG. 7 is a table illustrating analytical characteristics of calibration lines fitted to peak absorbance values for multiple different dye samples according to an example embodiment.
  • FIG. 8 is a graph illustrating calibration curves of absorbance values for different photometer embodiments and a laboratory
  • FIG. 9A is a graph illustrating correlation plots of peak absorbance values for different photometer embodiments and a laboratory spectrophotometer according to an example embodiment.
  • FIG. 9B is a graph illustrating correlation plots of chromogenic compounds peak absorbance values for different photometer embodiments and a laboratory spectrophotometer according to an example embodiment.
  • FIG. 10 is a table showing a comparison of analytical characteristics of correlations lines fitted to peak absorbance values for different photometer embodiments and a laboratory spectrophotometer according to an example embodiment.
  • FIGs. 11 A, 1 IB, and 11C are graphs illustrating absorbance of various samples versus wavelength according to an example embodiment.
  • FIG. 12 is a block diagram of programmable circuitry to perform methods, execute apps and applications, and process images according to example embodiments.
  • FIG. 13 is flowchart illustrating a method performing image based photometry according to an example embodiment.
  • FIG. 14 is a flowchart illustrating a method of accounting for spatial gradients in an intensity of broadband light of an image based photometer according to an example embodiment.
  • the software may consist of computer executable instructions stored on one or more non-transitory storage devices. Examples of such non-transitory storage devices include computer readable media or computer readable storage devices such as one or more memory or other type of hardware based storage devices, either local or networked and other non-transitory storage devices.
  • the term "module" may be used to represent code stored on a storage device for execution by circuitry, such as one or more processors, which together form specifically programmed circuitry or computer. Modules may also include combinations of code, circuitry, firmware or any combination thereof capable of performing functions associated with the module. Multiple functions may be performed in one or more modules as desired, and the embodiments described are merely examples.
  • the code or software may be executed on a digital signal processor, ASIC, microprocessor, or other type of processor operating on a computer system, such as a personal computer, server or other computer system.
  • Photometry of one or more samples is performed using a light source to illuminate the samples on one side of the samples and measuring light transmitted through the samples by RGB based imaging sensors.
  • RGB based imaging sensors By using transmitted, rather than reflected or scattered light, this approach enables simple, reproducible measurements of broadband absorbance calculated using the RGB color values (RGB-resolved absorbance) of the image of each sample.
  • the samples may be imaged using a flatbed scanner operating in transmittance mode. Multiple samples may be held in a microtiter plate, such as a 96 well plate. In a further embodiment, the plate with samples may be placed on a planar light source within a chamber and imaged by a camera, such as a smartphone or tablet based camera. One or more pixels corresponding to the transmittance of each sample may be used to calculate the RBG resolved absorbance which can be compared to RGB resolved absorbance values of known samples to identify each sample.
  • FIG. 1 is a perspective block schematic diagram of a photometer
  • the camera 110 may be a cellphone based camera in one embodiment, such as for example, an LG OPTFMUS F3 4G LTE.
  • the camera 110 is supported by a box 115, which may be formed of cardboard covered with black fabric, metal, plastic, or other opaque material to reduce or eliminate external light from reaching a detection region within the box.
  • a low-cost (US$6) planar light source 120 is positioned in the box 115 opposite the camera 110.
  • the box 115 also has a hole about the size of a camera lens, such as a 6-mm hole, with the camera 110 body blocking external light from entering the hole.
  • the planar light source 120 may be an edge-lit LED backlight module, such as that currently found in many smartphones and tablet computers.
  • the inside of the box forms a detection region, with the light source 120 serving to illuminate samples 125 from below.
  • the samples which may be wells of a microtiter plate 126, are thus positioned between the light source and camera such that the camera receives light transmitted through the samples.
  • the plate 126 maybe placed directly on top of the light source 120 such that it is supported by the light source 120. Guides may be used to repeatably and consistently position the plate 126 on the light source 120. Utilizing light transmitted from a uniform light source 120 provides a high- quality absorbance measurement.
  • the alignment between the light source 120 and the detector (camera) establishes an optical path length that is simple, well- defined, and spatially uniform across the plate containing samples.
  • the box 115 may have four sides and a top having a size in one embodiment to define a fixed imaging distance of 15.5 cm and to provide a field of view sufficient to capture light transmitted through the samples.
  • the top of the box 115 in one embodiment has the hole for the camera.
  • the top of the box is thus a sensing surface positioned opposite the light source to receive light transmitted through the multiple wells.
  • the box 115 may also operate to shield ambient light from transmission through the wells.
  • a base 127 may be used in one embodiment to mate with the box
  • the base 127 in one embodiment may be formed by adhering a sheet of foam (1" thick) underneath a perfboard provided a surface on which to solder components and fix them in place.
  • a series circuit consisting of two 9-V batteries 130 may be connected electrically in parallel and in separate battery holders, a toggle switch 135, a potentiometer 140 (to adjust brightness), and the planar light source 120.
  • the box may 1 15 be placed on the base 127.
  • the hole may be formed with the use of a biopsy punch, and may be centered on the planar light source 120, for the camera 110.
  • potentiometer 140 may be located outside of the box for easy access. [0048] If the light source 120 is smaller than the microtiter plate 126
  • the plate 126 may be moved to capture multiple images which may cover all the wells of the plate.
  • the planar light source may be large enough to illuminate 32 wells of a standard 96-microtiter plate. In this arrangement, three separate images may be obtained, moving the plate 126 between each image acquisition to capture the entire plate 126.
  • a larger backlight may be used to illuminate an entire sample set of the plate 126, and the box may be sized and camera optics selected to provide a field of view of an entire illuminate plate in one image.
  • the settings on the camera of the cell phone are identical to the settings on the camera of the cell phone.
  • LG OPTIMUS F3 4G LTE during image capture were set to the following: i) Focus: Auto, ii) ISO: 400, iii) White balance: Auto, iv) Brightness: 0.0, v) Image size: 5M (2560x 1920), vi) Color effect: None. Images may be saved as Joint Photographic Experts Group (JPEG) files in one embodiment, which was a default of the camera. In some embodiments, the box 115 may be folded and the entire photometer 100 may be stored in a small bag.
  • JPEG Joint Photographic Experts Group
  • a flatbed scanner 200 may be used to obtain images of samples as illustrated in a perspective view in FIG. 2.
  • One example flatbed scanner suitable for operating as part of a photometer is an Epson Perfection V500 photo, Epson ($90 USD) employing a CCD image sensor in a strip, and operating in transmittance mode.
  • the transmittance mode is designed for imaging photographic films, and uses a built-in transparency unit that employs a planar light source in a strip 210. Both the light source of the transparency unit and the image sensor scan across the imaging surface of the scanner simultaneously to capture an image of a 96-well microtiter plate 215 containing samples placed onto the imaging surface of the scanner.
  • the imaging area of the flatbed scanner in transmittance mode (27 cm x 8.3 cm) is large enough to image up to two standard microtiter plates in parallel.
  • All automatic correction functions may be unselected or disabled to ensure that the captured photometric data are not manipulated. Images may be saved as JPEG files.
  • FIG. 3 is a top view of an image of 96 well microtiter plate 400.
  • different wells of the plate 300 may be filled with different color dyes in each row, with the first four columns containing a different concentration than the second four columns, with the last row, row 12, containing a blank solution. Note that in transmittance mode for both image based photometers (100 and 200), the image of plate 400 illustrates that the RGB color value obtained is substantially uniform across the well.
  • the solutions of the dyes may be prepared in one embodiment with the following concentrations. Disperse orange 3 (2.81 , 8.43, 14.05, 28.10, 42.15, 56.20 ⁇ ), methyl orange (0.06, 0.24, 0.50, 1.00, 2.00, 4.00 ⁇ ), fluorescein (2.00, 4.00, 6.00, 8.00, 10.00, 16.00 uM), DPPH (1.40, 2.81 , 5.62, 8.43, 1 1.24, 16.86, 22.48, 28.10 uM), eosin Y (0.54, 1.00, 2.00, 2.69, 6.00, 8.00, 10.00, 13.45 ⁇ ), rhodamine B (0.16, 0.78, 1.17, 2.91 , 3.92, 5.83, 8.74, 1 1.66 ⁇ ), trypan blue (1.04, 2.08, 4.16, 6.24, 8.33, 10.41, 16.65, 20.82 ⁇ ), prussian blue (1.00, 2.00, 4.00, 6.00, 10.00, 14.
  • RGB-resolved absorbance Ak of each sample can be calculated using the following equation ( A k
  • RGB values may be read.
  • an eyedropper tool may be used to select a pixel, then colors are selected, edit colors selected, and define custom colors. This results in a display of RGB values which may be read.
  • the following procedure may be used. For each assay, first capture a baseline image of 3 blank solutions and then calculate for each well. Next, capture the sample image of, for example, 32 wells filled with 28 samples and 4 blank solutions. To account for any changes in the white balance from image to image (cell phone cameras typically adjust white balance automatically), estimate a white balance
  • RGB-resolved absorbance values obtained with photometers 100 and 200 may be compared to the peak absorbance values obtained using a microplate spectrophotometer. Calibration lines of absorbance versus concentration may also be prepared using the microplate spectrophotometer, the photometer 100, and the photometer 200 to verify the correlation between the RGB-resolved absorbance values and the peak absorbance values
  • Chromogenic compounds that exhibit absorbance peaks with very different spectral characteristics e.g., shape, position, and intensity of the spectral peak
  • Images of the microtiter plates that contain these solutions may be captured using the photometers 100 and 200.
  • RGB values of three pixels may then be read. The pixels may be chosen at random from within the image of each of the wells that contained solutions of the test compounds, using Image J or Microsoft Paint.
  • Mean values Ck of each group of RGB values may be recorded. The recorded values may then be used to estimate the broadband, RGB-resolved absorption Ak, for each color channel.
  • the present embodiments utilize light transmitted through a sample.
  • the alignment between the light source and the detector establishes an optical path length to an imaging device that is simple, well- defined, and spatially uniform across the plate.
  • the plate 300 may contain a bar code 310 that identifies the plate and may also indicate which wells contain specific reagents that may react with a sample.
  • the bar code may be visible in one or more images of the plate 300 and may be decoded to obtain the information identifying the plate and wells containing reagents.
  • the information identifying the wells containing reagents and the reagents in such wells may be provided via a lookup table pointed to by information in the bar code.
  • FIG. 4A is a histogram illustrating green channel pixel values of an image of a well containing 8.00 ⁇ Eosin Y solution captured using the flatbed scanner 200 in transmittance mode.
  • FIG. 4B is a histogram illustrating green channel pixels values of a well obtained in reflectance mode. Note the wide variation in values compared to the green channel values of in FIG. 4A corresponding to the scanner operating in transmission mode.
  • FIG. 4C is a histogram of green channel pixel values of the well obtained by a scanner using
  • FIG. 4D is a table providing statistical characteristics of the different methods of obtaining green channel pixel values from FIGs. 4A-4C.
  • FIG. 5 A is a histogram illustrating green channel pixel values of an image of a well containing 8.00 uM Eosin Y solution captured using the image based photometer 200.
  • FIG. 5B is a histogram illustrating green channel pixel values of an image of a well containing 8.00 uM Eosin Y solution captured using a cell phone camera in FIG. 5B relying on ambient light.
  • the RSD value of color values of all pixels within each well is less than 0.006.
  • This characteristic vastly reduces the image processing necessary to measure transmittance, simplifies the procedure, and makes it feasible without any specialized software.
  • the RGB values of three pixels chosen at random from the image of each well may be averaged.
  • the distribution of the color values of the pixels in each well is broad.
  • the mean and mode of the pixel values differed by 20.9%. This large difference indicates that the distribution of pixel values was not unimodal (in this case, bimodal).
  • the mean and mode of the pixel values differed by 10.3%. This large difference indicates that the distribution of pixel values was not unimodal.
  • photometers based on imaging devices e.g., scanners, cell phone cameras
  • RGB-based photodetectors that detect light over a broad bandwidth.
  • Digital imaging devices use image sensors, which consist of an array of pixel sensors, to convert light intensity to electrical current.
  • ⁇ ⁇ I (X)- S k ( )d where ⁇ ) define the range of wavelengths over which the sensor can detect light.
  • Equation 5 The RGB-resolved absorbance Au of the sample (with measured color value c ⁇ ) to a blank solution (with measured color value C ⁇ ), is defined by Equation 5. Substitution of Equation 3 into Equation 4 yields Equation 5, which relates Ak to Asfi) and ⁇ ( ⁇ ) :
  • RGB-based sensors Sufi) and yt are not provided by the manufacturers and vary between different imaging devices, and therefore, may be estimated experimentally.
  • Spectral sensitivity and gamma correction factors for all the color channels of the photometers 100 and 200 may be estimated in one embodiment by using an external light source, a monochromator, and a fiber optic cable to deliver pseudo delta-function inputs to the pixel sensors and determining the relationship between measured color values and sensitivity of each color channel. Further details of the estimation process are provided below. Note that manufacturers of scanners and light sources may also provide such estimates for each device.
  • FIG. 6A and FIG. 6E respectively show examples of
  • the L( ) of the light source of photometer 100 and the planar light source of the photometer 200 ii) the ⁇ ( ⁇ ) of 1 1 different dyes measured at a range of concentrations by the microplate spectrophotometer, and iii) the extracted values of Sufi) and 3 ⁇ 4 the expected Ak was estimated for all the standard compounds.
  • Equation 5 and the measured color values Gt measured Ak was calculated for all the standard compounds.
  • FIGs. 6A, 6B, 6C, 6D, 6E, 6F, 6G, and 6H outline the steps to estimate Ak for a 10- ⁇ solution of methylene blue for both the photometer 100 - FIGs. 6A-6D and the photometer 200 FIGs. 6E-6H.
  • FIGs. 6B and 6F illustrate transmittance versus wavelength
  • FIGs. 6C and 6G illustrate imaging sensor spectral sensitivity versus wavelength
  • FIGs. 6D and 6H illustrated intensity versus wavelength of captured light.
  • FIGs. 6D and 6H are graphs illustrating intensity of captured light, enable establishment of simple guidelines for which of the R, G, or B values should be used to calculate the RGB-resolved absorbance of compounds that absorb in different wavelengths. For a given wavelength, the channel that provided the highest sensitivity should be chosen.
  • FIGs. 6C and 6G show that the blue channel (B) of the CMOS/CCD detectors of the photometer 100 and the photometer 200 is most sensitive, compared to red and green channels, to light of wavelength between 400-505 nm, the green channel is the most sensitive to light of 505-580 nm, and the red channel to light of 580-700 nm.
  • the blue color channel may be used; for peaks in the region of 505- 580 nm, the green channel; and for peaks in the region of 580-700 nm, the red color channel.
  • R, G, or B values were selected for one embodiment because: i) most digital imaging devices use the RGB color system to digitize the image; ii) RGB values of the pixels of an image are easily read using commonly available software (e.g. Microsoft Paint, Adobe Illustrator, Image J); iii) RGB values can be considered as metrics of the total light intensity within certain bandwidths corresponding to the light that passes through the red, green and blue filters that are present on the surface of the CCD/CMOS photodetector.
  • the intensity of the gray scale value (x) and the hue (H) component of hue-saturation- value (HSV) color system are other parameters that have been used in the past to correlate the color of the sample with the concentration of an analyte. These values are simply linear (gray scale) or nonlinear (hue) combinations of the recorded RGB values, and are defined by Equation 7 and 8.
  • Spectral peaks typically overlap most strongly with only one RGB color channel. Combining these RGB values into grayscale or HSV values, therefore, adds information about light intensity that is not related to the concentration of the sample, and consequently, makes these color values less sensitive to changes in concentration than the raw RGB values.
  • FIG. 8 shows the calibration curve of absorbance values for DPPH vs concentration.
  • the curves were linear, and the limits-of-detection of concentration of the dyes, measured by both the microplate spectrophotometer and the low-cost photometers, were comparable as observable in table 700.
  • Equation 5 shows that this behavior occurs for at least two reasons: the polychromatic nature of RGB-resolved absorbance and the gamma correction. Relative to a standard narrowband measurement at X pea k, broadening the optical bandwidth of the measurement and misaligning X pea k with respect to the peak value of L(X)-Sk ( ⁇ ) can only serve to decrease the sensitivity to changes in concentration. This effect occurs because ⁇ L(X)- 10 " ⁇ ( ⁇ ) ⁇ & )dX includes regions oiA(X) that are less absorptive than A pea k.
  • the light that does not interact much (or at all) with the analyte will contribute more to the raw RGB color values ⁇ than light near pea k; in this case, the ratio between the raw RGB values, captured from the light transmitted through the sample relative to the blank, will tend to unity ⁇ 3 ⁇ 4 ' , and therefore, reduce the value of
  • solutions of rhodamine B and eosin Y that exhibit similar values oiA pea k as well as overall spectral shape ⁇ ( ⁇ ), shown in graphs of absorbance versus wavelength (nm) in FIGs. 1 1 A, 1 IB, and 1 1 C, may still exhibit very different values of green-resolved absorbance AG ( ⁇ 3-4x difference) because, compared to eosin Y, the position of pea k of rhodamine B is better- aligned with the peak of L(X) -SG(X).
  • FIG. 1 1 A shows absorbance spectra of disperse orange 3 in ethanolic solution (7.0 ⁇ ), methyl orange in aqueous solution (29.3 ⁇ ), and fluorescein in aqueous solution (20.0 ⁇ ).
  • FIG. 1 1B shows absorbance spectra of DPPH in methanolic solution (16.8 ⁇ ), eosin Y in aqueous solution (8.0 ⁇ ), and rhodamine B in aqueous solution (5.8 ⁇ ).
  • FIG. 1 1 A shows absorbance spectra of disperse orange 3 in ethanolic solution (7.0 ⁇ ), methyl orange in aqueous solution (29.3 ⁇ ), and fluorescein in aqueous solution (20.0 ⁇ ).
  • FIG. 1 1B shows absorbance spectra of DPPH in methanolic solution (16.8 ⁇ ), eosin Y in aqueous solution (8.0 ⁇ ), and rhodamine B in aqueous solution (5.8 ⁇ ).
  • the nonlinear gamma correction that all imaging equipment imposes also serves to distort the magnitude of ⁇ .
  • the gamma corrections always tended to further reduce Ak compared to a narrowband measurement centered at X pea k.
  • the gamma correction reduces the sensitivity to changes in
  • any image sensor can be calibrated easily for linear measurements of absorbance without express knowledge of the values of the gamma correction factors.
  • Image based photometers can, in principle, also enable quantification and discrimination between unknown concentrations of colored compounds in a mixture if they satisfy the following three criteria: i) the three values of Ak for each constituent compound are known (for example, at a standard, known concentration); ii) there are no more than three different compounds in the mixture (this condition arises because there are only three degrees of freedom in each measurement: AR, AG, and AB); iii) the values of Ak of the different compounds are linearly independent-that is, the column vectors
  • a single photometric measurement may be used to estimate the concentrations of each of the three compounds.
  • the Ak are not linearly independent-as may be the case if some or all of the absorption peaks occur within the same color channel- or if discrimination between more than three compounds is desired, it may be possible to satisfy these condition by adding extra degrees of freedom, for example, by comparing multiple measurements with and without narrow band color filters.
  • FIG. 12 is a block schematic diagram of a computer system 1200 to implement methods, execute apps, execute applications, and process images according to example embodiments. All components need not be used in various embodiments.
  • One example computing device in the form of a computer 1200 may include a processing unit 1202, memory 1203, removable storage 1210, and non-removable storage 1212.
  • the example computing device is illustrated and described as computer 1200, the computing device may be in different forms in different embodiments.
  • the computing device may instead be a smartphone, a tablet, smartwatch, or other computing device including the same or similar elements as illustrated and described with regard to FIG. 12.
  • Devices such as smartphones, tablets, and smartwatches are generally collectively referred to as mobile devices.
  • the various data storage elements are illustrated as part of the computer 1200, the storage may also or alternatively include cloud-based storage accessible via a network, such as the Internet.
  • Memory 1203 may include volatile memory 1214 and nonvolatile memory 1208.
  • Computer 1200 may include - or have access to a computing environment that includes - a variety of computer-readable media, such as volatile memory 1214 and non-volatile memory 1208, removable storage 1210 and non-removable storage 1212.
  • Computer storage includes random access memory (RAM), read only memory (ROM), erasable programmable readonly memory (EPROM) & electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD ROM), Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices capable of storing computer-readable instructions for execution to perform functions described herein.
  • RAM random access memory
  • ROM read only memory
  • EPROM erasable programmable readonly memory
  • EEPROM electrically erasable programmable read-only memory
  • flash memory or other memory technologies
  • Computer 1200 may include or have access to a computing environment that includes input 1206, output 1204, and a communication connection 1216.
  • Output 1204 may include a display device, such as a touchscreen, that also may serve as an input device.
  • the input 1206 may include one or more of a touchscreen, touchpad, mouse, keyboard, camera, one or more device-specific buttons, one or more sensors integrated within or coupled via wired or wireless data connections to the computer 1200, and other input devices.
  • the computer may operate in a networked environment using a communication connection to connect to one or more remote computers, such as database servers, including cloud based servers and storage.
  • the remote computer may include a personal computer (PC), server, router, network PC, a peer device or other common network node, or the like.
  • the communication connection may include a Local Area Network (LAN), a Wide Area Network (WAN), cellular, WiFi, Bluetooth, or other networks.
  • Computer-readable instructions stored on a computer-readable storage device are executable by the processing unit 1202 of the computer 1200.
  • a hard drive, CD-ROM, and RAM are some examples of articles including a non-transitory computer-readable medium such as a storage device.
  • the terms computer-readable medium and storage device do not include carrier waves.
  • a computer program 1218 capable of providing a generic technique to perform access control check for data access and/or for doing an operation on one of the servers in a component object model (COM) based system may be included on a CD-ROM and loaded from the CD-ROM to a hard drive.
  • the computer-readable instructions allow computer 1200 to provide generic access controls in a COM based computer network system having multiple users and servers.
  • COM component object model
  • a processor readable storage device has instructions to cause a circuit based processor to perform operations 1300 as illustrated in flowchart form in FIG. 13.
  • the operations may include receiving an image at 1310 of multiple samples based on broadband white light directed through the multiple samples.
  • the image may then be viewed or otherwise opened to allow access to pixel information at 1315.
  • pixel information at 1315.
  • RGB red, green, and blue
  • the averaged values may then be correlated to provide an RGB-resolved absorbance of each sample to identify each sample at 1335.
  • the correlation may be performed via a lookup table in some embodiments with RGB-resolved absorbance correlated to a value of the sample to identify the sample, identify a concentration of the sample, or determine another parameter.
  • operations on the images may account for spatial gradients in an intensity of the broadband white light as indicated at operations 1400 in FIG. 14.
  • Operations 1400 may begin by receiving at 1410 a baseline image of multiple blank solution samples held in multiple wells of a multiple well plate. Also, a sample image of multiple wells filed with samples is received at 1415, wherein some of the wells are filled with the blank solution.
  • a while balance correction factor is estimated based on the RGB values of the blank solution samples in the baseline image and RGB values of the blank solution samples in the sample image.
  • an RGB-resolved absorbance of each sample is determined as a function of the correction factor as previously described in detail.
  • An image based photometer comprising:
  • a light source adapted to hold a well plate having multiple wells for testing samples, the light source providing a source of broadband white light for transmission through the multiple wells;
  • a sensing surface positioned opposite the light source to receive light transmitted through the multiple wells and shield ambient light from
  • sensing surface comprises a container having a top and four sides with an opening in the top positioned above the light source to support a camera to obtain images of the well plate through the opening.
  • the light source is a planar light source
  • a battery supported by the base and coupled to provide power to the light source
  • a switch coupled to the battery to control provision of the power to the light source.
  • a method comprising:
  • RGB red, green, and blue
  • identifying the multiple well microtiter plate comprises reading and decoding a bar code on the microtiter plate.
  • JPEG joint picture experts group
  • RGB values are obtained from an image of the samples and a program executing on a processor to extract red green, and blue (RGB) values for multiple pixels corresponding to each sample.
  • a processor readable storage device having instructions to cause a circuit based processor to perform operations comprising:
  • RGB red, green, and blue

Abstract

L'invention concerne un photomètre basé sur des images qui comprend une source lumineuse conçue pour maintenir une plaque à puits comprenant de multiples puits pour des échantillons à tester, la source lumineuse consistant une source de lumière blanche à large bande destinée à être transmise à travers les multiples puits. Une surface de détection est placée à l'opposé de la source lumineuse pour recevoir la lumière transmise à travers les multiples puits et empêcher la lumière ambiante d'être transmise à travers les puits.
PCT/US2016/044245 2015-07-27 2016-07-27 Photométrie basée sur des images WO2017019762A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201562197300P 2015-07-27 2015-07-27
US62/197,300 2015-07-27

Publications (1)

Publication Number Publication Date
WO2017019762A1 true WO2017019762A1 (fr) 2017-02-02

Family

ID=57885308

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2016/044245 WO2017019762A1 (fr) 2015-07-27 2016-07-27 Photométrie basée sur des images

Country Status (1)

Country Link
WO (1) WO2017019762A1 (fr)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
IT201800004498A1 (it) * 2018-04-13 2019-10-13 Apparato e metodo per determinare parametri fisici e chimici di un campione disomogeneo tramite acquisizione ed elaborazione di immagini a colori del campione
CN112816480A (zh) * 2021-02-01 2021-05-18 奎泰斯特(上海)科技有限公司 水质酶底物鉴定方法
CN112924421A (zh) * 2021-01-28 2021-06-08 重庆邮电大学 一种核酸适配体传感器的共振光散射检测分析方法及检测装置
US11222735B2 (en) 2016-02-29 2022-01-11 Liquid Wire Inc. Deformable conductors and related sensors, antennas and multiplexed systems
US11585705B2 (en) 2016-02-29 2023-02-21 Liquid Wire Inc. Sensors with deformable conductors and selective deformation

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6233065B1 (en) * 1997-03-26 2001-05-15 Mustek Systems, Inc. Scanner with transmission-mode scanning function
US20070177156A1 (en) * 2003-07-18 2007-08-02 Daniel Mansfield Surface profiling method and apparatus
US20070263954A1 (en) * 2001-09-27 2007-11-15 Bio-Rad Laboratories, Inc. Biochemical assay detection in a liquid receptacle using a fiber optic exciter
US20090073275A1 (en) * 2005-06-01 2009-03-19 Kouhei Awazu Image capturing apparatus with flash device

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6233065B1 (en) * 1997-03-26 2001-05-15 Mustek Systems, Inc. Scanner with transmission-mode scanning function
US20070263954A1 (en) * 2001-09-27 2007-11-15 Bio-Rad Laboratories, Inc. Biochemical assay detection in a liquid receptacle using a fiber optic exciter
US20070177156A1 (en) * 2003-07-18 2007-08-02 Daniel Mansfield Surface profiling method and apparatus
US20090073275A1 (en) * 2005-06-01 2009-03-19 Kouhei Awazu Image capturing apparatus with flash device

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11222735B2 (en) 2016-02-29 2022-01-11 Liquid Wire Inc. Deformable conductors and related sensors, antennas and multiplexed systems
US11585705B2 (en) 2016-02-29 2023-02-21 Liquid Wire Inc. Sensors with deformable conductors and selective deformation
US11955253B2 (en) 2016-02-29 2024-04-09 Liquid Wire Inc. Deformable conductors and related sensors, antennas and multiplexed systems
IT201800004498A1 (it) * 2018-04-13 2019-10-13 Apparato e metodo per determinare parametri fisici e chimici di un campione disomogeneo tramite acquisizione ed elaborazione di immagini a colori del campione
WO2019197952A1 (fr) * 2018-04-13 2019-10-17 Universita' Degli Studi Di Modena E Reggio Emilia Appareil et procédé de détermination de paramètres physiques et chimiques d'un échantillon non homogène par acquisition et traitement d'images couleurs de l'échantillon
CN112924421A (zh) * 2021-01-28 2021-06-08 重庆邮电大学 一种核酸适配体传感器的共振光散射检测分析方法及检测装置
CN112816480A (zh) * 2021-02-01 2021-05-18 奎泰斯特(上海)科技有限公司 水质酶底物鉴定方法

Similar Documents

Publication Publication Date Title
US8493441B2 (en) Absorbance measurements using portable electronic devices with built-in camera
US9506855B2 (en) Method and system for analyzing a colorimetric assay
CN112074725B (zh) 基于精确比色法的检测试纸读取器系统
WO2017019762A1 (fr) Photométrie basée sur des images
US7557924B2 (en) Apparatus and methods for facilitating calibration of an optical instrument
US10514335B2 (en) Systems and methods for optical spectrometer calibration
TWI832873B (zh) 用於偵測樣品中的分析物之偵測方法
de Carvalho Oliveira et al. RGB color sensor for colorimetric determinations: Evaluation and quantitative analysis of colored liquid samples
US20100239137A1 (en) Two Dimensional Imaging of Reacted Areas On a Reagent
Nixon et al. Accurate device-independent colorimetric measurements using smartphones
CN112964652A (zh) 一种溶液比色分析快速检测装置、系统和检测方法
Scheeline Smartphone technology–instrumentation and applications
US20170160189A1 (en) Optical analysis system and process
CN214584857U (zh) 一种溶液比色分析快速检测装置、系统
RU2791099C2 (ru) Способ определения для определения аналита в образце
KR101383338B1 (ko) 엘이디와 포토트랜지스터를 이용한 반사형 색 정보 측정 장치 및 이를 이용한 측정방법
RU2791101C2 (ru) Способ оценки пригодности условий освещения для определения аналита в образце с применением камеры мобильного устройства
US11397148B2 (en) Method of analyzing liquid samples, microplate reader and computer program
Agudo-Acemel Digitization of colorimetric measurements for quantitave analyses using a smartphone
WO2023209466A1 (fr) Colorimétrie utilisant un colorimètre portable

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 16831287

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 16831287

Country of ref document: EP

Kind code of ref document: A1