Analyzer and method for detecting occult blood within a sample

Abstract

Disclosed herein is a method in which pixel data of an image of a pad is analyzed to locate non-hemolyzed red blood cells (NH-RBC) in a urine sample on the pad by conducting a denoising operation on the pixel data to remove noise from the pixel data and to generate highlighted pixel data containing background data (BD) and an enhanced representation of the NH-RBC relative to the BD. A thresholding operation is conducted on the highlighted pixel data to generate thresholded pixel data distinguishing the enhanced representation of the NH-RBC from the BD. A first amount of the enhanced representation of the NH-RBC relative to a second amount of the BD in the thresholded pixel data is determined. An identifier is stored in a memory indicative of the first amount of the enhanced representation of the NH-RBC relative to the second amount of the BD in the thresholded pixel data.

Description

ANALYZER AND METHOD FOR DETECTING OCCULT BLOOD WITHIN A SAMPLE

[0001] This application claims benefit under 35 USC § 119(e) of U.S. Provisional Application No. 63 / 639,141 , filed April 26, 2024. The entire contents of the above-referenced patent application are hereby expressly incorporated herein by reference.BACKGROUND

[0002] Occult blood (OB) or blood in a urine sample which cannot be seen with the naked eye is challenging to diagnose. OB indicates an underlying health condition that needs medical attention. In urine OB can come from the urinary system, which includes bladder, kidney, genitals, urinary tract or prostate. And this condition could be of various severity from simple urinary tract infection to kidney disease to prostate cancer.

[0003] Occult blood detection has been done using a microscope or other advanced diagnostic techniques. Occult blood in a urine sample can also be detected using urine testing strips such as Siemens Healthineers urine chemistry strip, for instance. Composition of chemistry pads used for detection of occult blood include, for instance, 6.8% w / w Di-isopropyl benzene Di hydroperoxide and an indicator, Tetra methyl benzidine (TMB). Hemoglobin from the blood cells acts as peroxidase and catalyzes the liberation of oxygen from organic peroxide. Oxidized TMB in turn changes color from orange to green-blue. If the red blood cells (RBC) or erythrocytes in urine are intact, or non-hemolyzed, they may produce a speckle on the pad, or, if in a group, they will produce a cluster of speckles. At times when one or more of the red blood cells have burst, or is hemolyzed, as known in the art, it will turn the yellowish orange chemistry pad to different shades of bluish-green. All these different characteristics of speckle and different shade of occult blood chemistry pad colors are based on number of red blood cells, non-hemolyzed or hemolyzed present in the urine sample.

[0004] Even though the number of speckles on the urine pad are countable, sometimes due to smudging or clusters, individual speckles may become difficult todifferentiate. Similarly, the shades of bluish-green color are subjective and interpretation varies from person to person.

[0005] Depending on severity and patient condition, occult blood is detected using several advanced diagnostic techniques like microscopy, cystoscopy, and CT scan. Using a chemistry-based urine test, OB can be measured with the user’s eyes, but results are extremely subjective. OB strips can also be measured on a CCD based detection system, illuminated with a multiwavelength light source system. In this case, the system measures the standard deviation (SD) of the OB pad, due to the changes in color gradation with a urine sample and match the color gradation with a threshold. This approach, however, is not robust enough to differentiate between a hemolyzed sample and different levels of non-hemolyzed samples, as computation of SD on the raw signals is susceptible to variations caused by several factors, such as environmental noise, and device electronic noise. The noise causes this algorithm to provide a substantial number of false negatives. One urinalysis product named Chemstrip 10, used in a Urinalysis Test System, has the ability to detect blood in urine. Chemstrip 10 can differentiate between hemolyzed blood and non-hemolyzed blood. However, Chemstrip 10 cannot differentiate between different levels in a sample of non-hemolyzed blood within the urine sample. The Applicant of the present patent application, i.e., Siemens Healthcare Diagnostics, has a reagent strip for urinalysis that tests for occult blood in urine that can differentiate intact red blood cells as trace and moderate.

[0006] Accordingly, a need exists in the art for methods and systems that can consistently and accurately quantify different clinical levels of hemolyzed and non- hemolyzed occult blood in urine samples.SUMMARY

[0007] In one embodiment, the presently disclosed inventive concepts is a method and a reagent analyzer that locates occult blood in urine samples by analyzing pixel data of an image of a wet reagent pad to locate non-hemolyzed red blood cells in a urine sample deposited on the wet reagent pad. The wet reagent pad is positioned within a housing of a reagent analyzer. In some embodiments, analyzing the pixel data comprises conducting a denoising operation on the pixel data to remove noise from the pixel data and to generate highlighted pixel data containing background data and an enhanced representation of the non-hemolyzed red blood cells relative to the background data; conducting a thresholding operation on the highlighted pixel data togenerate thresholded pixel data distinguishing the enhanced representation of the non-hemolyzed red blood cells from the background data; determining a first amount of the enhanced representation of the non-hemolyzed red blood cells relative to a second amount of the background data in the thresholded pixel data; and storing an identifier in a non-transitory computer readable medium indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells relative to the second amount of the background data in the thresholded pixel data.

[0008] In another embodiment, the present invention describes a reagent analyzer, comprising a housing configured to receive a wet reagent pad, a camera situated in the housing, the camera configured to capture an image of the wet reagent pad; and a controller having a processor and a non-transitory computer readable medium, the non-transitory computer readable medium storing instructions that, when executed, cause the processor to analyze pixel data of an image of a wet reagent pad captured by the camera to locate non-hemolyzed red blood cells in a urine sample deposited on the wet reagent pad, wherein analyzing the pixel data comprises: conducting a denoising operation on the pixel data to remove noise from the pixel data and to generate highlighted pixel data containing background data and an enhanced representation of the non-hemolyzed red blood cells relative to the background data; conducting a thresholding operation on the highlighted pixel data to generate thresholded pixel data distinguishing the enhanced representation of the non- hemolyzed red blood cells from the background data; determining a first amount of the enhanced representation of the non-hemolyzed red blood cells relative to a second amount of the background data in the thresholded pixel data; and storing an identifier in the non-transitory computer readable medium indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells relative to the second amount of the background data in the thresholded pixel data.

[0009] The foregoing Summary provides an overview of certain selected implementations or embodiments disclosed herein, and is not intended to describe every aspect, embodiment, implementation, feature, or advantage of the disclosure exhaustively or comprehensively. Therefore, this Summary should not be construed in such a way to limit the scope of this disclosure or to limit the scope of the claims. The details of one or more implementation or embodiment disclosed herein are set forth in the accompanying drawings and descriptions below. Other aspects, features,implementations, embodiments, and advantages will become readily apparent in view of the description, the drawings, and the claims set forth herein.BRIEF DESCRIPTION OF THE DRAWINGS

[0010] To assist those of ordinary skill in the relevant art in making and using the inventive concepts disclosed herein, reference is made to the appended drawings and schematics, which are not intended to be drawn to scale, and in which like reference numerals are intended to refer to the same or similar elements for consistency. For purposes of clarity, not every component may be labeled in every drawing. Certain features and certain views of the figures may be shown exaggerated and not to scale or in schematic in the interest of clarity and conciseness. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. In the drawings:

[0011] FIG. 1 is a front elevation view of an exemplary embodiment of an analyzer according to the inventive concepts disclosed herein, showing a transparent shield positioned in a field of view of an imaging system thereof.

[0012] FIG. 2 is a side elevation view of the analyzer of FIG. 1 .

[0013] FIG. 3 is a side elevational view the analyzer of FIG. 1 having an aperture surrounded by one or more illumination source according to the inventive concepts disclosed herein.

[0014] FIG. 4 is a flow diagram of an exemplary embodiment of a method for determining a presence and amount of occult blood in a urine sample using the analyzer of FIG. 1 in accordance with the inventive concepts disclosed herein.

[0015] FIG. 5 illustrates exemplary images processed using the method of FIG. 4 in accordance with the inventive concepts disclosed herein.DETAILED DESCRIPTION

[0016] Before explaining at least one embodiment of the inventive concepts disclosed herein in detail, it is to be understood that the inventive concepts are not limited in their application to the details of construction and the arrangement of the components or steps or methodologies set forth in the following description or illustrated in the drawings. The inventive concepts disclosed herein are capable of other embodiments or of being practiced or carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein is for thepurpose of description and should not be regarded as limiting the inventive concepts disclosed and claimed herein in any way.

[0017] In the following detailed description of embodiments of the inventive concepts, numerous specific details are set forth in order to provide a more thorough understanding of the inventive concepts. However, it will be apparent to one of ordinary skill in the art that the inventive concepts disclosed herein may be practiced without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the instant disclosure.

[0018] As used herein, the terms "comprises," "comprising," "includes," "including," "has," "having" or any other variation thereof, are intended to cover a nonexclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherently present therein.

[0019] Unless expressly stated to the contrary, "or" refers to an inclusive or and not to an exclusive or. For example, a condition A or B is satisfied by anyone of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present).

[0020] In addition, use of the "a" or "an" are employed to describe elements and components of the embodiments herein. This is done merely for convenience and to give a general sense of the inventive concepts. This description should be read to include one or at least one and the singular also includes the plural unless it is obvious that it is meant otherwise.

[0021] Further, as used herein any reference to "one embodiment" or "an embodiment" means that a particular element, feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment.

[0022] As used herein “wet reagent test device” refers to a reagent device that has a volume of sample deposited thereon such that the reagent in the reagent device may react with its target constituent if such constituent is present in the sample. A wet reagent test device may also have a volume of a negative control deposited thereon.

[0023] As used herein, “reagent test device” refers to a carrier having a reagent. Exemplary reagent devices include a reagent pad of a dip and read test strip, or a control strip or a test strip of a lateral flow immunoassay.

[0024] Finally, as used herein qualifiers such as “about,” “approximately,” and “substantially” are intended to signify that the item being qualified is not limited to the exact value specified, but includes some slight variations or deviations therefrom, caused by measuring error, manufacturing tolerances, stress exerted on various parts, wear and tear, and combinations thereof, for example.

[0025] The inventive concepts disclosed herein are generally directed to an method and system for an imaging based, smaller footprint urinalysis system, which used general purpose CMOS camera sensors. The method and system may be an automatic and robust semi-quantitative call out procedure, that can reliably call-out occult blood results and translate the visual result into a clinically relevant outcome, that aids in medical diagnosis.

[0026] Referring now to FIGS. 1-3, shown therein is an exemplary embodiment of a reagent analyzer 10 according to the inventive concepts disclosed herein. The reagent analyzer 10 may be an automatic reagent card analyzer, for example. Exemplary embodiments of automatic reagent card analyzers are described in detail in U.S. patent application Serial No. 13 / 712,144, filed on December 12, 2012, and in PCT application No. PCT / US2012 / 069621 , filed on December 14, 2012, the entire disclosures of which are hereby expressly incorporated herein by reference.

[0027] Generally, the exemplary reagent analyzer 10 may include a housing 14, having a slot 15, the housing 14 surrounding a cavity 18. The reagent analyzer 10 also includes, at least one rail 19, an imaging system 22 comprising at least a camera 26, a sample tray 30 having a sample holder 32 positioned within the cavity 18, a transparent shield 31 , and a circuit board 34 having an aperture 38 and one or more illumination source 42a-n positioned within the cavity 18.

[0028] The housing 14 may be formed from one or more components configured to form the cavity 18 and support the at least one rail 19, imaging system 22, the sample tray 30, the transparent shield 31 , and the circuit board 34. In one embodiment, the housing 14 is opaque to visible light. In another embodiment, the housing 14 is opaque to one or more wavelength of light generated by the one or more illumination source 42a-n. In one embodiment, the housing 14 may normalize ambient light. In other non-limiting embodiments, the housing 14 has the slot 15 within which the transparent shield 31 may be positioned into the housing 14, and from which the transparent shield 31 may be removed from within the housing 14.

[0029] The transparent shield 31 has at least one sidewall 33, at least one end 35, a first surface 36 extending between the at least one sidewall 33 and the at least one end 35, a second surface 37 positioned opposite the first surface 36 extending between the at least one sidewall 33 and the at least one end 35, and an intermediate region 41 extending between the first surface 36 and the second surface 37. In one non-limiting embodiment, the transparent shield 31 has a first end 35a, a second end 35b positioned opposite the first end 35a, the first surface 36 extending from the first end 35a to the second end 35b, the second surface 37 positioned opposite the first surface 36 extending from the first end 35a to the second end 35b, and the intermediate region 41 extending between the first surface 36 and the second surface 37. In one embodiment, the transparent shield 31 is transparent to visible light such that light may travel through the transparent shield 31 without appreciable scattering allowing objects positioned beyond the transparent shield 31 to be seen and imaged clearly. In some embodiments, the transparent shield 31 may have a degree of translucence such that light may travel through the transparent shield 31 with scattering allowing objects positioned beyond the transparent shield 31 to be seen with varying degrees of clarity. The first surface 36 and the second surface 37 may both be planar and substantially parallel so as to avoid magnifying visible light passing through the transparent shield 31. As will be discussed in more detail below, the transparent shield 31 is configured to protect the imaging system 22 from splatter or other debris resulting from movement of the sample tray 30 into and out of the housing 14. In some non-limiting embodiments, the transparent shield 31 may be movable within and out of the housing 14 through the slot 15. For example, the transparent shield 31 may have a grip (not shown) on at least one end 35 of the transparent shield 31 . The grip may be a textured surface, e.g., a frost or an etching on the first surface 36 and / or the second surface 37, or may include a handle extending from and / or connected to the first surface 36 and / or the second surface 37, or the like.

[0030] In some non-limiting embodiments, the at least one rail 19 may be positioned within the cavity 18, adjacent to the slot 15 such that upon the positioning of the transparent shield 31 within the slot 15, the surface 37 of the transparent shield 31 may be positioned on the at least one rail 19. In other non-limiting embodiments, the at least one rail 19 may be positioned within the cavity 18, adjacent to the slot 15 such that upon positioning the transparent shield 31 within the slot 15, the surface 36 of the transparent shield 31 may be positioned on the at least one rail 19.

[0031] The imaging system 22 includes the at least one camera 26 and is supported by the housing 14. In one embodiment, the imaging system 22 may be fixed to the housing 14 or fixed at a relative distance from the sample tray 30 or the transparent shield 31 , for example. The imaging system 22 and / or the camera 26 may include one or more lens with a focal length selected to provide a field of view 40 to include at least the aperture 38 of the circuit board 34.

[0032] The imaging system 22 may be implemented and function as any desired reader such that the field of view 40 of the imaging system 22 includes substantially the entire aperture 38 of the circuit board 34, for example. The imaging system 22 may be supported at a location above, below, or beside the sample tray 30. In some embodiments, the field of view 40 may extend in a linear direction from the imaging system 22 to the aperture 38. In other embodiments, the field of view 40 may extend in a non-linear direction from the imaging system 22 to the aperture 38 due to the presence of one or more optical steering component in the field of view 40. Exemplary optical steering components include mirror(s), lens(es), beam splitter(s), or combinations thereof. The imaging system 22 may be configured to detect or capture an image or an optical signal indicative of a reflectance value or a color value of a reagent pad, a lateral flow assay, or the like, positioned in the field of view 40 of the imaging system 22, for example. In other non-limiting embodiments, the imaging system 22 may be configured to detect or capture an image or an optical signal indicative of a reflectance value or a color value of the sample holder 32 positioned in the field of view 40 of the imaging system 22, through the transparent shield 31. It is to be understood, however that in some exemplary embodiments, the field of view 40 of the imaging system 22 may include only a portion of the aperture 38 of the circuit board 34. It is also to be understood, that in some exemplary embodiments, field of view 40 of the imaging system may include only a portion of the transparent shield 31 . The camera 26 of the imaging system 22 may include any desired digital or analog imager, such as a digital camera, an analog camera, a CMOS imager, a diode, and combinations thereof. The imaging system 22 may also include a lens system, optical filters, collimators, diffusers, or any other optical-signal processing devices, for example. Further, the imaging system 22 is not limited to an optical imager in the visible spectrum, and may include an infrared imaging system, an ultra-violet imaging system, a microwave imaging system, an X-ray imaging system, and / or other desired imaging systems, for example. Non-exclusive examples of the imaging system 22include optical imaging systems, spectrophotometers, gas chromatographs, microscopes, infrared sensors, and combinations thereof, for example.

[0033] In one embodiment, the imaging system 22 includes at least one camera 26 and lens wherein the at least one camera 26 is an AR0239: CMOS Image Sensor, 2.3 MP, 1 / 2.7” and the lens is a DSL949 Sunex lens (Sunex Inc., Carlsbad, CA), both configured to maintain a large field of view 40 while keeping geometric image distortion low, thereby providing a resolution of 1080 pixels by 1920 pixels wherein each pixel depicts approximately a 0.065mm square area of the sample tray 30 and / or the sample holder 32.

[0034] The sample tray 30 may be configured to adjust the location of the sample holder 32 within the field of view 40. The sample holder 32 may be configured to receive at least one of test device 44, which may be a reagent card or a reagent card cassette, each having a sample 46. The sample 46 may be any bodily fluid, tissue, or any other chemical or biological sample, and combinations thereof other than blood, such as urine, or saliva, for example. The sample 46 may be in liquid form and may contain one or more target constituents such as bilirubin, ketones, glucose, or any other desired target constituent, for example.

[0035] The housing 14 may include a plurality of connected sidewalls 80, 82, 84 and 86 cooperating to surround the cavity 18. The sidewall 80 is spaced from the sidewall 82, and the sidewall 84 is spaced from the sidewall 86. The transparent shield 31 may be sized and dimensioned to traverse the cavity 18 between the sidewalls 80 and 82, and the sidewalls 84 and 86 thereby dividing the cavity 18 into a first portion 88 and a second portion 90. In some embodiments, the transparent shield 31 may have a length L between approximately 5 cm and approximately 21 cm. In some nonlimiting embodiments, the transparent shield 31 may be a protecting device for the lens, wherein the transparent shield 31 may have a length of approximately 5 cm. In other non-limiting embodiments, the transparent shield 31 may be a protecting device for the lens and the optical components, wherein the transparent shield 31 may have a length of approximately 14 cm. In some non-limiting embodiments, wherein the transparent shield 31 is a protecting device for the lens and the optical components, the transparent shield 31 may not be removable from the reagent analyzer 10.

[0036] In some embodiments, the housing 14 has the slot 15, and the transparent shield 31 is positioned within the cavity 18 adjacent to the slot 15. In some embodiments, the surface 36 and the surface 37 of the transparent shield 31 areplanar and parallel within the intermediate region 41 to avoid distorting or scattering light passing through the transparent shield 31. The transparent shield 31 may be separate from the imaging system 22 and configured to block debris originating from the sample tray 30 from coming into contact with the imaging system 22. The transparent shield 31 may be constructed of glass, ceramic, plastic, such as acrylic, polycarbonate, and the like.

[0037] The illumination source 42a-n may be implemented as one or more of a light emitting diode, a light bulb, a laser, an incandescent bulb or tube, a fluorescent light bulb or tube, a halogen light bulb or tube, or any other desired light source or object configured to emit an optical signal having any desired intensity, wavelength, frequency, or direction of propagation, for example. The illumination source 42a-n may be attached to the circuit board 34 and may be oriented such that substantially the entire field of view 40 of the imaging system 22 is illuminated by the illumination source 42a-n. In some exemplary embodiments, the illumination source 42a-n may be operably coupled with a controller 144 (see FIG. 3 - described in detail below) so that control and / or power signals may be supplied to the illumination source 42a-n by the controller 144. Desirably, the intensity of the optical signal emitted by the illumination source 42a-n is maintained substantially constant through the operation of the reagent analyzer 10, such as by control and power signals supplied by the controller 144. In one embodiment, the optical signals emitted by the illumination source 42a-n may be conditioned or processed by one or more optical or other systems (not shown), such as filters, diffusers, polarizers, lenses, lens systems, collimators, and combinations thereof, for example.

[0038] In some exemplary embodiments the one or more illumination source 42a-n may be implemented, such as a first illumination source 42a and a second illumination source 42b, and the first illumination source 42a and the second illumination source 42b may have different locations and / or orientations thereby causing the first illumination source 42a and the second illumination source 42b to cooperate to illuminate substantially the entire field of view 40 of the imaging system 22. (e g., substantially the entire sample holder 32 and / or sample 46). The first illumination source 42a and the second illumination source 42b may emit optical signals having different illumination intensities, for example.

[0039] In one embodiment, the sample holder 32 may be adapted to accept the test device 44 in the form of a reagent card cassette having one or more multiple-profile reagent cards therein, for example. The test device 44 may include a substrate and one or more reagent pads positioned thereon, or otherwise associated therewith. In an exemplary embodiment, the reagent pads may include fluidic or microfluidic compartments (not shown).

[0040] Each reagent pad may include a reagent configured to undergo a color change in response to the presence of a target constituent such as occult blood or substance in the sample 46 of a specimen deposited on the reagent pad. The reagent pads may be provided with different reagents for detecting the presence of different target constituents. Different reagents may cause one or more color change in response to the presence of a certain constituent in the sample 46, such as a certain type of analyte. The color developed by a reaction of a particular constituent with a particular reagent may define a characteristic discrete spectrum for absorption and / or reflectance of light for that particular constituent. The extent of color change of the reagent and the sample 46 may depend on the amount of the target constituent present in the sample 46, for example.

[0041] The presence and concentrations of these target constituents in the sample 46 may be determinable by an analysis of the color changes undergone by the one or more reagent pads at predetermined times after application of the sample 46 to the reagent pads and / or at predetermined read positions in the field of view of the imaging system 22, for example. This analysis may involve a color comparison of each reagent pad to itself at different time periods after application of the sample 46 and / or at different read positions in the field of view 40 of the imaging system 22.

[0042] Based upon an analysis of a magnitude of the optical signal detected by the imaging system 22 the sample 46 may be assigned to one of a number of categories, e.g., a first category corresponding to no target constituent present in the sample 46, a second category corresponding to a small concentration of target constituent present in the sample 46, a third category corresponding to a medium concentration of target constituent present in the sample 46, and a fourth category corresponding to a large concentration of target constituent present in the sample 46, for example.

[0043] Further, the imaging system 22 may detect an optical signal indicative of a color or a reflectance value of a reagent pad and / or a test strip at any time interval after a volume of sample 46 has been dispensed on the test device 44, e.g., the reagent pad and / or test strip, and regardless of location of the particular reagent padand / or test strip, for example. In one exemplary embodiment, a video, or a sequence of images may be captured of the reagent pad and / or test strip at a variety of time intervals after a volume of sample 46 is deposited on the reagent pad and / or test strip.

[0044] The imaging system 22 may be operated intermittently, continuously, or periodically, to detect one or more reflectance signals indicative of the color or the reflectance value of the one or more test devices 44, e.g., reagent pads, at any time and at any position in the field of view of the camera 26, for example. In some exemplary embodiments, the imaging system 22 may capture an image indicative of the color or the reflectance value of the test device 44, e.g., the reagent pad, prior to any sample 46 being deposited onto the reagent pad, or at any known time after a volume of sample 46 has been deposited onto the reagent pad, for example.

[0045] Referring now to FIG. 3, shown therein is an analyzer diagram 140 depicting the reagent analyzer 10 including an analyzer controller 144, and a display 146. The display 146 can be monitor using any suitable technology such as liquid crystal display technology, light emitting diode display technology, or the like. The analyzer controller 144 has at least a processor 148 coupled to a non-transitory computer readable medium 152. The non-transitory computer readable medium can be random access memory, read-only memory or the like and can be located locally with the processor 148 or remotely (e.g., in the cloud). The non-transitory computer readable medium 152 can be formed of any suitable medium, such as a magnetic medium, a semiconductor medium or optical medium. The non-transitory computer readable medium 152 may store computer executable instructions that, when executed by the processor 148, causes the processor 148 to communicate with and / or be operably coupled to other elements of the reagent analyzer 10, such as the display 146, the non-transitory computer readable medium 152, the imaging system 22, and the illumination source 42. While the analyzer controller 144 is depicted separately from the reagent analyzer 10, it is understood that in some embodiments, the analyzer controller 144 may be integrated into the reagent analyzer 10, such as, by way of example only, the analyzer controller 144 may be an additional component of the reagent analyzer 10 or may be integrated with another component of the reagent analyzer 10, for example, the circuit board 34.

[0046] In one embodiment, the imaging system 22 may be operably coupled with the analyzer controller 144 and / or the processor 148 so that one or more power and / or control signals may be transmitted to the camera 26 and / or to the one or moreillumination source 42a-n by the controller 144, and so that one or more signals may be transmitted from the camera 26 of the imaging system 22 to the processor 148, for example. The analyzer controller 144 may be configured to gauge test results as a reagent card is sampled within the reagent analyzer 10, for example, by receiving one or more signals from the camera 26. The camera 26 may be configured to detect or capture one or more optical or other signals through the transparent shield 31 that are indicative of a reflectance value of the test device 44, such as a reagent pad, and to transmit a signal indicative of the reflectance value of the test device 44, e.g., the reagent pad, to the processor 118, for example. One or more optical signals having wavelengths indicative of a reflectance value of the reagent pads and / or the test strip may be detected through the transparent shield 31 by the camera 26 at each read position, for example. The camera 26 may detect an optical signal through the transparent shield 31 indicative of a reflectance value of a reagent pad and / or test strip at any desired read position, location, or area within the field of view 40, or any other desired location or area or multiple locations or areas, for example. The signal transmitted to the processor 148 by the camera 26 may be an electrical signal, an optical signal, and combinations thereof, for example. In one embodiment, the signal is in the form of an image file having a matrix of pixels, with each pixel having a color code indicative of a reflectance value. In an exemplary embodiment, the image file may have two or more predetermined regions of pixels, each predetermined region of pixels corresponding to a read position of one of the reagent pads, a calibration strip, and / or the test strip in the field of view 40 of the camera 26. In one embodiment, the processor 148 may store the signal transmitted and or the image file in one or more database 156 and / or in the non-transitory computer readable medium 152.

[0047] The processor 148 may determine the reflectance value or the color change of reagent pad and / or a test strip along with a sample (e.g., urine) disposed on the reagent pad and / or test strips based on the signals detected by the camera 26, for example. Each optical or other signal indicative of one or more reflectance value readings detected by the camera 26 may have a magnitude relating to a different wavelength of light (i.e., color). The color of the sample(s) and / or the reaction of the one or more reagents with a target constituent in a reagent pad may be determined based upon the relative magnitudes of the reflectance signals of various color components, for example, red, green, and blue reflectance component signals. For example, the color of each reagent pad may be translated into a standard color model,which typically includes three or four values or color components (e.g., RGB color model, including hue, saturation, and lightness (HLS) and hue, saturation, and value (HSV) representation of points and / or CMYK color model, or any other suitable color model) whose combination represents a particular color. In some embodiments the camera 26 may detect multiple optical signals at each read position, with each detected signal having one or more color components, such as a red component signal, a green component signal, and a blue component signal, forexample, and each of the component signals may be transmitted to the processor 148. In some exemplary embodiments, the camera 26 may detect a single optical signal at each read position, and the processor 148 may translate a signal received from the camera 26 into separate color component signals such as a red component signal, a green component signal, and a blue component signal, for example.

[0048] In one embodiment, a method 400 for identifying and differentiating between different levels of non-hemolyzed and hemolyzed red blood cells in a urine sample may be implemented as a set of processor executable instructions or logic stored in the non-transitory computer readable medium, which instructions or logic when executed by the processor 148, cause the processor 148 to determine whether or not the occult blood in the urine sample is hemolyzed or non-hemolyzed, and a clinical level of the non-hemolyzed blood in the sample.

[0049] In step 402, the camera captures an image of the test device 44, such as a reagent pad having a sample, e.g., urine, to be analyzed for occluded blood.

[0050] In optional step 404, when the captured image is a color image, such as an RGB image, for instance, the processor 148 converts the captured image into a grayscale image. The captured image may be converted to grayscale using any of the approaches known or which may become known in the art, such as a lightness method (an average of the highest and lowest color space pixel values for a pixel), or an average method (an average of all of the color space pixel values for a pixel), of a luminosity method. All of these methodologies are known in the art.

[0051] In step 406, noise may be removed from the grayscale image by conducting a denoising operating on the pixel data to remove noise from the pixel data and to generate highlighted pixel data containing background data and an enhanced representation of any non-hemolyzed red blood cells relative to the background data. For instance, morphological erosion and dilation operations may be applied to the grayscale image using a ball shaped structuring element for removal of noise andhighlighting any specks that are caused due to any whole red blood cells in nonhemolyzed blood present in the urine sample.

[0052] In step 408, a thresholding operation may be conducted on the highlighted pixel data to generate thresholded pixel data distinguishing the enhanced representation of the non-hemolyzed red blood cells from the background data. Thresholding may be performed on the processed image to obtain a threshold value, for instance, that allows the processor 148 to distinguish between the urinalysis chemistry pad background and / or hemolyzed blood and the whole red blood cells, if present. For instance, in one embodiment, Otsu thresholding may be used.

[0053] In optional step 410, the processed image may be converted to a binary image. Converting the processed image to the binary image allows a constant offset to be applied to the threshold value to fine tune the detection of non-hemolyzed red blood cells. A binary image is a digital image that contains only two pixel values, typically 0 and 1. In this type of image, 0 usually represents black, and 1 represents white, making the image strictly monochrome. In some embodiments, black pixels represent non-hemolyzed red blood cells and white pixels represent background or hemolyzed blood.

[0054] In step 412, the processor 148 determines a number, if any, of speckles (representing non-hemolyzed blood cells) in the binary image. For instance, when speckles are present, first pixel values representing speckles (i.e., whole blood cells or non-hemolyzed blood) in the binary image will be differentiated from second pixel values representing the background. The amount of non-hemolyzed red blood cells may be determined by determining a first amount of the first pixel values representing the non-hemolyzed red blood cells relative to a second amount of the second pixel values representing the background data. A standard deviation (SD) of the binary image can be used to compute a presence of non-hemolyzed blood along with an approximate number of RBC based on speckles. The approximate number of RBC can be computed in a variety of manners. For example, a machine vision technique known in the art as “blob analysis” can be performed by the processor 148 to differentiate between hemolyzed and non-hemolyzed blood. Blob analysis is a technique of machine vision that analyzes consistent image regions that are discernible from the background. Once one or more image regions are identified indicative of RBCs (the first pixel values), the image regions can be analyzed to estimate the number of RBCs. This can be accomplished by determining parameterssuch as area, eccentricity, connectivity, or the like to get an approximate count of RBC involved in each image region. The image regions identified in the binary image may also be used to identify the image regions in the image captured by the camera 26. Then, the processor 148 may be programmed to inspecting color intensity of the original image in the image regions, to determine an approximate number of RBC present in the image region. Alternatively, the processor 148 may be programmed to use standard image segmentation models trained through machine learning I artificial intelligence algorithms to extract RBC speckles in a binary or color image (e.g., the original image or the thresholded image) to differentiate between hemolyzed and nonhemolyzed RBC along with arriving at an approximate number of non-hemolyzed RBC present on the reagent pad.

[0055] In step 414, the number of speckles counted in step 412 is compared with a predetermined threshold stored in the non-transitory computer readable medium 152. In some embodiments, the predetermined threshold may be computed based on a series of experiments, for instance, and stored in the non-transitory computer readable medium 152. In general, the series of experiments may be conducted by applying different levels (negative, trace, small, moderate and large) of hemolyzed and (trace, moderate) non-hemolyzed blood samples to one or more reagent pad on a reagent strip, and then analyzing the one or more reagent pad on a test reagent analyzer similar to the reagent analyzer 10. The data collected by the test reagent analyzer is analyzed and an observed standard deviation, pattern and number of red blood cells may be used to obtain the threshold. Once the predetermined threshold is obtained, the predetermined threshold can be saved in the non-transitory computer readable medium 152 of the reagent analyzer 10.

[0056] To differentiate between non-hemolyzed and hemolyzed occult blood in the sample, the processor 148 may be programmed to determine if the number of speckles counted in step 412 is equal to or greater than the predetermined threshold. If the speckles counted in step 412 are equal to or greater than the predetermined threshold, the processor 148 determines that the occult blood in the urine sample is non-hemolyzed. If the speckles counted in step 412 are less than the predetermined threshold, the processor 148 determines that the occult blood in the urine sample is Hemolyzed.

[0057] In step 416, the processor 148 may be programmed to determine a clinical level of the non-hemolyzed blood in the urine sample. For instance, theprocessor 148 may compare the number of speckles to two or more ranges associated with two or more clinical levels. For instance, the clinical levels may be a first clinical level representing a trace amount of non-hemolyzed blood and a second clinical level representing a moderate amount of non-hemolyzed blood. In some embodiments, the clinical levels may include a negative clinical level indicating that there was no non- hemolyzed blood in the urine sample.

[0058] In step 418, the processor 148 may be programmed to store an identifier in the non-transitory computer readable medium 152 indicative of the clinical level of the non-hemolyzed blood. In some embodiments, the identifier may be a first amount of the enhanced representation of the non-hemolyzed red blood cells relative to the second amount of the background data in the thresholded pixel data. In some embodiments, the processor 148 may be programmed to cause the system to display on the display 146 the clinical level in format readable by a human to aid in medical diagnosis.

[0059] Referring now to FIG. 5, shown therein is a visual representation of images 502, 504, 506 and 508 as the images are processed using the method 400. Image 502 is a raw image of a reagent pad treated with a volume of a sample, such as urine. The image 502 may be captured, in color, using the camera 26 such as in step 402.

[0060] Image 504 is a grayscale image that represents a grayscale image as processed in step 404. Rather than processing the color image into the grayscale image, the grayscale image can be captured by the camera 26.

[0061] Image 506 is a denoised image that represents an image as denoised in step 406.

[0062] Image 508 is a thresholded image that represents an image as processed in step 408. The image 508 includes one or more first pixels 510 indicative of non-hemolyzed red blood cells and one or more second pixels 512 indicative of a background data.

[0063] The following is a number list of non-limiting illustrative embodiments of the inventive concept disclosed herein:

[0064] Illustrative Embodiment 1. A method, comprising: analyzing pixel data of an image of a wet reagent pad to locate non-hemolyzed red blood cells in a urine sample deposited on the wet reagent pad, thewet reagent pad positioned within a housing of a reagent analyzer, wherein analyzing the pixel data comprises: conducting a denoising operation on the pixel data to remove noise from the pixel data and to generate highlighted pixel data containing background data and an enhanced representation of the non-hemolyzed red blood cells relative to the background data; conducting a thresholding operation on the highlighted pixel data to generate thresholded pixel data distinguishing the enhanced representation of the non-hemolyzed red blood cells from the background data; and determining a first amount of the enhanced representation of the non- hemolyzed red blood cells relative to a second amount of the background data in the thresholded pixel data; and storing an identifier in a non-transitory computer readable medium indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells relative to the second amount of the background data in the thresholded pixel data.

[0065] Illustrative Embodiment 2. The method of illustrative embodiment 1 , wherein the image is a color image and the method further comprises converting the color image to a grayscale image before conducting the denoising operation on the pixel data.

[0066] Illustrative Embodiment 3. The method of illustrative embodiment 1 , wherein the image is a grayscale image.

[0067] Illustrative Embodiment 4. The method of any one of illustrative embodiments 1-3, wherein the thresholded pixel data is converted to binary pixel data to form a binary image, wherein the binary pixel data representing the non-hemolyzed blood cells have a first pixel value and the binary pixel data representing the background data have a second pixel value; and wherein determining the amount of the non-hemolyzed red blood cells is performed by determining a first amount of the first pixel values representing the non- hemolyzed red blood cells relative to a second amount of the second pixels values representing the background data.

[0068] Illustrative Embodiment 5. The method of illustrative embodiment 4, wherein determining the amount of non-hemolyzed red blood cells includes determining at least one of an area, eccentricity, or connectivity of the first pixel values.

[0069] Illustrative Embodiment 6. The method of illustrative embodiment 4, wherein determining the amount of non-hemolyzed red blood cells includes identifying one or more image regions containing the first pixel values, using the one or more image regions in the binary image to identify one or more image regions in the image, and analyzing the one or more image regions in the image to determine the amount of non-hemolyzed red blood cells.

[0070] Illustrative Embodiment 7. The method of illustrative embodiment 6, wherein analyzing the one or more image regions in the image is defined further as inspecting color intensity within the one or more image regions.

[0071] Illustrative Embodiment 8. The method of any one of illustrative embodiments 1-7, wherein the thresholded pixel data is converted to binary pixel data to form a binary image, wherein the binary pixel data representing the non-hemolyzed blood cells have a first pixel value and the binary pixel data representing the background data have a second pixel value; and wherein determining the amount of the non-hemolyzed red blood cells is performed by using image segmentation models trained through machine learning I artificial intelligence algorithms to analyze the binary pixel data and determine an approximate number of non-hemolyzed RBC present on the wet reagent pad.

[0072] Illustrative Embodiment 9. The method of illustrative embodiment 1 , wherein the image of the wet reagent pad is a color image, and wherein determining the amount of the non-hemolyzed red blood cells is performed by using image segmentation models trained through machine learning I artificial intelligence algorithms to analyze at least one of the thresholded pixel data and / or the color image to determine an approximate number of non-hemolyzed RBC present on the wet reagent pad.

[0073] Illustrative Embodiment 10. The method of any one of illustrative embodiments 1-9, wherein the identifier indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells is compared to at least two ranges, a first one of the at least two ranges representing a first clinical level of non- hemolyzed blood and a second one of the at least two ranges representing a second clinical level of non-hemolyzed blood to determine a clinical level of non-hemolyzed blood in the urine sample.

[0074] Illustrative Embodiment 11. The method of illustrative embodiment 10, wherein the analyzer is provided with a display and the clinical level of non-hemolyzed blood in the urine sample is output on the display.

[0075] Illustrative Embodiment 12. A reagent analyzer, comprising: a housing configured to receive a wet reagent pad; a camera situated in the housing, the camera configured to capture an image of the wet reagent pad; and a controller having a processor and a non-transitory computer readable medium, the non-transitory computer readable medium storing instructions that, when executed, cause the controller to analyze pixel data of an image of a wet reagent pad captured by the camera to locate non-hemolyzed red blood cells in a urine sample deposited on the wet reagent pad, wherein analyzing the pixel data comprises: conducting a denoising operation on the pixel data to remove noise from the pixel data and to generate highlighted pixel data containing background data and an enhanced representation of the non-hemolyzed red blood cells relative to the background data; conducting a thresholding operation on the highlighted pixel data to generate thresholded pixel data distinguishing the enhanced representation of the non-hemolyzed red blood cells from the background data; and determining a first amount of the enhanced representation of the non- hemolyzed red blood cells relative to a second amount of the background data in the thresholded pixel data; and storing an identifier in the non-transitory computer readable medium indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells relative to the second amount of the background data in the thresholded pixel data.

[0076] Illustrative Embodiment 13. The reagent analyzer of illustrative embodiment 12, wherein the camera is configured to capture images in color and the instructions are configured to cause the controller to convert the color image to a grayscale image before conducting the denoising operation on the pixel data.

[0077] Illustrative Embodiment 14. The reagent analyzer of illustrative embodiment 12, wherein the camera is configured to capture images in grayscale.

[0078] Illustrative Embodiment 15. The reagent analyzer of any one of illustrative embodiments 12-14, wherein the instructions cause the controllerto convert the thresholded pixel data to binary pixel data to form a binary image, wherein the binary pixel data representing the non-hemolyzed blood cells have a first pixel value and the binary pixel data representing the background data have a second pixel value; and wherein determining the amount of the non-hemolyzed red blood cells is performed by determining a first amount of the first pixel values representing the non- hemolyzed red blood cells relative to a second amount of the second pixels values representing the background data.

[0079] Illustrative Embodiment 16. The reagent analyzer of illustrative embodiment 15, wherein the instructions cause the controller to determine the amount of non-hemolyzed red blood cells by determining at least one of an area, eccentricity, or connectivity of the first pixel values.

[0080] Illustrative Embodiment 17. The reagent analyzer of illustrative embodiment 15, wherein the instructions cause the controller to determine the amount of non-hemolyzed red blood cells by identifying one or more image regions containing the first pixel values, using the one or more image regions in the binary image to identify one or more image regions in the image, and analyzing the one or more image regions in the image to determine the amount of non-hemolyzed red blood cells.

[0081] Illustrative Embodiment 18. The reagent analyzer of illustrative embodiment 17, wherein analyzing the one or more image regions in the image is defined further as inspecting color intensity within the one or more image regions.

[0082] Illustrative Embodiment 19. The reagent analyzer of any one of illustrative embodiments 12-18, wherein the instructions cause the controllerto convert the thresholded pixel data to binary pixel data to form a binary image, wherein the binary pixel data representing the non-hemolyzed blood cells have a first pixel value and the binary pixel data representing the background data have a second pixel value; and wherein determining the amount of the non-hemolyzed red blood cells is performed by using image segmentation models trained through machine learning I artificial intelligence algorithms to analyze the binary pixel data and determine an approximate number of non-hemolyzed RBC present on the reagent pad.

[0083] Illustrative Embodiment 20. The reagent analyzer of illustrative embodiment 12, wherein the image of the wet reagent pad is a color image, and wherein determining the amount of the non-hemolyzed red blood cells is performed by using image segmentation models trained through machine learning I artificial intelligence algorithms to analyze at least one of the thresholded pixel data and / or the color image to determine an approximate number of non-hemolyzed RBC present on the reagent pad.

[0084] Illustrative Embodiment 21. The reagent analyzer of any one of illustrative embodiments 12-20, wherein the instructions further cause the controller to compare the identifier indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells is compared to at least two ranges stored in the non-transitory computer readable medium, a first one of the at least two ranges representing a first clinical level of non-hemolyzed blood and a second one of the at least two ranges representing a second clinical level of non-hemolyzed blood to determine a clinical level of non-hemolyzed blood in the urine sample.

[0085] Illustrative Embodiment 22. The reagent analyzer of illustrative embodiment 21 , wherein the reagent analyzer is provided with a display and instructions cause the controller to cause the clinical level of non-hemolyzed blood in the urine sample to be output on the display.

[0086] From the above description, it is clear that the inventive concepts disclosed herein are well adapted to carry out the objects and to attain the advantages mentioned herein as well as those inherent in the inventive concepts disclosed herein. While exemplary embodiments of the inventive concepts disclosed herein have been described for purposes of this disclosure, it will be understood that numerous changes may be made which will readily suggest themselves to those skilled in the art and which are accomplished within the scope of the inventive concepts disclosed and as defined in the appended claims.

Claims

What is claimed is:1 . A method, comprising: analyzing pixel data of an image of a wet reagent pad to locate non-hemolyzed red blood cells in a urine sample deposited on the wet reagent pad, the wet reagent pad positioned within a housing of a reagent analyzer, wherein analyzing the pixel data comprises: conducting a denoising operation on the pixel data to remove noise from the pixel data and to generate highlighted pixel data containing background data and an enhanced representation of the nonhemolyzed red blood cells relative to the background data; conducting a thresholding operation on the highlighted pixel data to generate thresholded pixel data distinguishing the enhanced representation of the non-hemolyzed red blood cells from the background data; and determining a first amount of the enhanced representation of the non- hemolyzed red blood cells relative to a second amount of the background data in the thresholded pixel data; and storing an identifier in a non-transitory computer readable medium indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells relative to the second amount of the background data in the thresholded pixel data.

2. The method of claim 1 , wherein the image is a color image and the method further comprises converting the color image to a grayscale image before conducting the denoising operation on the pixel data.

3. The method of claim 1 , wherein the image is a grayscale image.

4. The method of any of claims 1-3, wherein the thresholded pixel data is converted to binary pixel data to form a binary image, wherein the binary pixel data representing the non-hemolyzed blood cells have a first pixel value and the binary pixel data representing the background data have a second pixel value; andwherein determining the amount of the non-hemolyzed red blood cells is performed by determining a first amount of the first pixel values representing the non-hemolyzed red blood cells relative to a second amount of the second pixels values representing the background data.

5. The method of claim 4, wherein determining the amount of non- hemolyzed red blood cells includes determining at least one of an area, eccentricity, or connectivity of the first pixel values.

6. The method of claim 4, wherein determining the amount of non- hemolyzed red blood cells includes identifying one or more image regions containing the first pixel values, using the one or more image regions in the binary image to identify one or more image regions in the image, and analyzing the one or more image regions in the image to determine the amount of non-hemolyzed red blood cells.

7. The method of claim 6, wherein analyzing the one or more image regions in the image is defined further as inspecting color intensity within the one or more image regions.

8. The method of any of claims 1-7, wherein the thresholded pixel data is converted to binary pixel data to form a binary image, wherein the binary pixel data representing the non-hemolyzed blood cells have a first pixel value and the binary pixel data representing the background data have a second pixel value; and wherein determining the amount of the non-hemolyzed red blood cells is performed by using image segmentation models trained through machine learning I artificial intelligence algorithms to analyze the binary pixel data and determine an approximate number of non-hemolyzed RBC present on the wet reagent pad.

9. The method of claim 1 , wherein the image of the wet reagent pad is a color image, and wherein determining the amount of the non-hemolyzed red blood cells is performed by using image segmentation models trained through machine learning / artificial intelligence algorithms to analyze at least one of the thresholdedpixel data and / or the color image to determine an approximate number of non- hemolyzed RBC present on the wet reagent pad.

10. The method of any one of claims 1 -9, wherein the identifier indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells is compared to at least two ranges, a first one of the at least two ranges representing a first clinical level of non-hemolyzed blood and a second one of the at least two ranges representing a second clinical level of non-hemolyzed blood to determine a clinical level of non-hemolyzed blood in the urine sample.11 . The method of claim 10, wherein the analyzer is provided with a display and the clinical level of non-hemolyzed blood in the urine sample is output on the display.

12. A reagent analyzer, comprising: a housing configured to receive a wet reagent pad; a camera situated in the housing, the camera configured to capture an image of the wet reagent pad; and a controller having a processor and a non-transitory computer readable medium, the non-transitory computer readable medium storing instructions that, when executed, cause the controller to analyze pixel data of an image of a wet reagent pad captured by the camera to locate non-hemolyzed red blood cells in a urine sample deposited on the wet reagent pad, wherein analyzing the pixel data comprises: conducting a denoising operation on the pixel data to remove noise from the pixel data and to generate highlighted pixel data containing background data and an enhanced representation of the non- hemolyzed red blood cells relative to the background data; conducting a thresholding operation on the highlighted pixel data to generate thresholded pixel data distinguishing the enhanced representation of the non-hemolyzed red blood cells from the background data;determining a first amount of the enhanced representation of the nonhemolyzed red blood cells relative to a second amount of the background data in the thresholded pixel data; and storing an identifier in the non-transitory computer readable medium indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells relative to the second amount of the background data in the thresholded pixel data.

13. The reagent analyzer of claim 12, wherein the camera is configured to capture images in color and the instructions are configured to cause the controller to convert the color image to a grayscale image before conducting the denoising operation on the pixel data.

14. The reagent analyzer of claim 12, wherein the camera is configured to capture images in grayscale.

15. The reagent analyzer of any one of claims 12-14, wherein the instructions cause the controller to convert the thresholded pixel data to binary pixel data to form a binary image, wherein the binary pixel data representing the nonhemolyzed blood cells have a first pixel value and the binary pixel data representing the background data have a second pixel value; and wherein determining the amount of the non-hemolyzed red blood cells is performed by determining a first amount of the first pixel values representing the non-hemolyzed red blood cells relative to a second amount of the second pixels values representing the background data.

16. The reagent analyzer of claim 15, wherein the instructions cause the controller to determine the amount of non-hemolyzed red blood cells by determining at least one of an area, eccentricity, or connectivity of the first pixel values.

17. The reagent analyzer of claim 15, wherein the instructions cause the controller to determine the amount of non-hemolyzed red blood cells by identifying one or more image regions containing the first pixel values, using the one or more image regions in the binary image to identify one or more image regions in the image, andanalyzing the one or more image regions in the image to determine the amount of non- hemolyzed red blood cells.

18. The reagent analyzer of claim 17, wherein analyzing the one or more image regions in the image is defined further as inspecting color intensity within the one or more image regions.

19. The reagent analyzer of any one of claims 12-18, wherein the instructions cause the controller to convert the thresholded pixel data to binary pixel data to form a binary image, wherein the binary pixel data representing the nonhemolyzed blood cells have a first pixel value and the binary pixel data representing the background data have a second pixel value; and wherein determining the amount of the non-hemolyzed red blood cells is performed by using image segmentation models trained through machine learning I artificial intelligence algorithms to analyze the binary pixel data and determine an approximate number of non-hemolyzed RBC present on the reagent pad.

20. The reagent analyzer of claim 12, wherein the image of the wet reagent pad is a color image, and wherein determining the amount of the non-hemolyzed red blood cells is performed by using image segmentation models trained through machine learning I artificial intelligence algorithms to analyze at least one of the thresholded pixel data and / or the color image to determine an approximate number of non-hemolyzed RBC present on the reagent pad.

21. The reagent analyzer of any one of claims 12-20, wherein the instructions further cause the controller to compare the identifier indicative of the first amount of the enhanced representation of the non-hemolyzed red blood cells is compared to at least two ranges stored in the non-transitory computer readable medium, a first one of the at least two ranges representing a first clinical level of non- hemolyzed blood and a second one of the at least two ranges representing a second clinical level of non-hemolyzed blood to determine a clinical level of non-hemolyzed blood in the urine sample.

22. The reagent analyzer of claim 21 , wherein the reagent analyzer is provided with a display and instructions cause the controller to cause the clinical level of non-hemolyzed blood in the urine sample to be output on the display.

Images