Consider the errors in optical measurement

Abstract

The described apparatus and method include placing at least a portion of a blood sample within a sample chamber (52) and obtaining a microscopic image of a portion of the blood sample. Candidates for a given entity within the blood sample are identified within the microscopic image. By performing further analysis on the candidates, at least some of the candidates are verified as the given entity. A count of candidates for the given entity is compared to a count of the verified candidates for the given entity, and at least in part based on the relationship between the count of candidates and the count of verified candidates, at least a portion of the sample is rendered invalid for use in performing at least some measurements on the sample. Other applications are also described.

Description

[0001] Cross - reference to related applications

[0002] This application claims priority to U.S. Provisional Patent Application No. 62 / 924,229, entitled "Accounting for errors in optical measurements", filed on October 22, 2019, by Pecker.

[0003] This application is related to a PCT application by Pecker, entitled "Accounting for errors in optical measurements", filed on the same date as this application, which claims priority to U.S. Provisional Patent Application No. 62 / 924,229, filed on October 22, 2019, by Pecker.

[0004] The applications mentioned above are incorporated herein by reference.

[0005] Field of embodiments of the invention

[0006] Some applications of the present disclosure generally relate to the analysis of body samples, and particularly to optical density and microscopic measurements of blood samples.

[0007] Background

[0008] In some optical - based methods (e.g., diagnostic and / or analytical methods), the properties of a biological sample, such as a blood sample, are determined by performing optical measurements. For example, the density of a component (e.g., the count of the component per unit volume) can be determined by counting the components within a microscopic image. Similarly, the concentration and / or density of a component can be measured by performing light absorption, transmission, fluorescence, and / or luminescence measurements on the sample. Typically, the sample is placed in a sample carrier, and measurements are performed on a portion of the sample contained within a chamber of the sample carrier. The measurements performed on the portion of the sample contained within the chamber of the sample carrier are analyzed in order to determine the properties of the sample.

[0009] Summary of embodiments

[0010] In some applications in accordance with the present invention, a biological sample (e.g., a blood sample) is placed into a sample carrier. When the sample is placed in the sample carrier, optical measurements are performed on the sample using one or more optical measurement devices. For example, the optical measurement devices can include microscopes (e.g., digital microscopes), spectrophotometers, photometers, spectrometers, cameras, spectral cameras, hyperspectral cameras, fluorometers, spectrofluorometers, and / or photodetectors (such as photodiodes, photoresistors, and / or phototransistors). For some applications, the optical measurement devices include dedicated light sources (such as light-emitting diodes, incandescent light sources, etc.) and / or optical elements (such as lenses, diffusers, filters, etc.) for manipulating light collection and / or light emission. For some applications, the microscope system used is generally similar to the microscope system described by Greenfield in US 2014 / 0347459, which is incorporated herein by reference.

[0011] A computer processor generally receives and processes the results of the optical measurements performed by the optical measurement devices. Additionally typically, the computer processor controls the acquisition of the results of the optical measurements performed by one or more optical measurement devices. For some applications, the optical measurement devices are housed within an optical measurement unit. To perform optical measurements on the sample, the sample carrier is placed within the optical measurement unit. Generally, the optical measurement unit includes a microscope system configured to perform microscopic imaging on a portion of the sample. For some applications, the microscope system includes a set of brightfield light sources (e.g., light-emitting diodes) configured for brightfield imaging of the sample, a set of fluorescence light sources (e.g., light-emitting diodes) configured for fluorescence imaging of the sample, and a camera (e.g., a CCD camera and / or a CMOS camera) configured to image the sample. Generally, the optical measurement unit also includes an optical density measurement unit configured to perform optical density measurements (e.g., light absorption measurements) on a second portion of the sample. For some applications, the optical density measurement unit includes multiple sets of optical density measurement light sources (e.g., light-emitting diodes) and light detectors configured to perform optical density measurements on the sample. For some applications, each of the above multiple sets of light sources (i.e., a set of brightfield light sources, a set of fluorescence light sources, and a set of optical density measurement light sources) includes multiple light sources (e.g., multiple light-emitting diodes), each light source being configured to emit light at a corresponding wavelength or corresponding wavelength band.

[0012] In some applications according to the present invention, various techniques are performed (usually by a computer processor) to determine whether various errors have occurred and, if so, optionally identify the source of the error. These errors may stem from the preparation of all samples. For example, before measurements are performed, the sample may have been in the sample carrier for too long (which may cause sample degradation, and / or which may cause the dye mixed with one or both parts of the sample to be overly absorbed by entities within the sample). Alternatively, the error may stem from the preparation of a particular part of the sample. Alternatively or additionally, the error may stem from an error in the sample carrier (such as the material of the sample carrier itself being unclean, and / or dirt or spilled blood on the sample carrier), and / or an error in the microscope system itself such as illumination (e.g., light-emitting diodes for bright-field imaging and / or light-emitting diodes used during fluorescence imaging of the sample), and / or an error associated with the optical path and / or motor and stage components or controllers, and / or an error caused by the environment in which the device is placed (e.g., relative humidity, temperature, pressure, particle concentration, or any other environmental factor). Additionally, alternatively or additionally, there may be inherent problems with the sample (such as a very low or very high count of a particular entity, or too much time having passed since sample collection was performed), which means that the computer processor cannot perform certain measurements with sufficient precision, and / or which means that the computer processor should flag this to the user.

[0013] For some applications, in response to identifying an error, the computer processor outputs a message indicating the error and / or indicating the source of the error. For some applications, the computer processor does not perform certain measurements on the blood sample in response to identifying an error. For some applications, in response to identifying an error, the computer processor does not perform any measurements on the sample, and / or flags the sample as invalid for the user, and / or instructs the user to repeat sample preparation with a new kit and / or recollect the blood sample. Alternatively or additionally, the computer processor determines certain parameters of the blood sample by calibrating the measurements performed on the blood sample in order to account for the error.

[0014] For some applications, for example, one or more of the following errors are accounted for in one or more of the above ways:

[0015] Errors in the microscopy device, such as:

[0016] - Step-loss of the motor moving the microscope stage

[0017] - Variation in backlash of the movement of the microscope stage

[0018] - Timing variation between the microscope camera and the microscope stage

[0019] - Alignment between the microscope camera and the microscope stage (e.g., due to relative rotation between these components)

[0020] - Problems with the optical system (e.g., changes in focus quality over time, e.g., caused by the sample or by a piece of the microscope stage (e.g., a scratched piece))

[0021] - Levelling variations in the microscope system

[0022] - Variations in the expected focus position along the z-axis (i.e., the optical axis)

[0023] - Loss of communication between components

[0024] - Variations in the linear response of the camera

[0025] Errors caused by environmental factors, such as:

[0026] - The device being outside the allowable temperature, humidity, altitude, etc.

[0027] - Specific components being outside the target values

[0028] General errors, caused by factors such as:

[0029] - Scanning time

[0030] - Device startup time

[0031] - Available working / storage memory

[0032] Some examples of techniques for identifying errors and addressing such errors are described below.

[0033] Thus, some applications according to the present invention provide a method, comprising:

[0034] Preparing a blood sample for analysis by the steps of:

[0035] Depositing the blood sample in a sample chamber; and

[0036] Placing the sample chamber in which the blood sample is deposited within a microscopic unit;

[0037] Obtaining one or more microscopic images of the sample chamber in which the blood sample is deposited using a microscope of the microscopic unit;

[0038] Based on the one or more images, determining the amount of one or more cell types that have sedimented within the sample chamber before obtaining the one or more microscopic images; and

[0039] Determining a characteristic of the sample, at least in part in response thereto.

[0040] In some applications, preparing a blood sample for analysis further includes staining the blood sample with one or more dyes.

[0041] In some applications:

[0042] Determining the amount of one or more cell types that have sedimented within the sample chamber before acquiring one or more microscopic images includes determining whether more than a threshold amount of red blood cells within the sample chamber have sedimented within the sample chamber before acquiring one or more microscopic images, and

[0043] Determining a characteristic of the sample includes: in response to determining that more than a threshold amount of red blood cells within the sample chamber have sedimented within the sample chamber before acquiring one or more microscopic images, invalidating at least a portion of the sample from being used to perform at least some measurements on the sample.

[0044] In some applications, the method further includes:

[0045] After placing the sample chamber in which the blood sample is deposited within the microscopy unit, allowing one or more cell types within the sample chamber to form a monolayer of cells;

[0046] Acquiring a set of one or more additional microscopic images of the monolayer of cells; and

[0047] Performing one or more measurements on the sample by analyzing the set of one or more additional microscopic images.

[0048] In some applications, the method further includes determining an indication of how long the blood sample has been present within the sample chamber before acquiring one or more microscopic images based on the amount of one or more cell types that have sedimented within the sample chamber before acquiring one or more microscopic images.

[0049] In some applications, the method further includes performing one or more measurements on the sample,

[0050] Determining the amount of one or more cell types that have sedimented within the sample chamber before acquiring one or more microscopic images includes determining whether more than a threshold amount of red blood cells within the sample chamber have sedimented within the sample chamber before acquiring one or more microscopic images, and

[0051] Performing one or more measurements on the sample includes: in response to determining that more than a threshold amount of red blood cells within the sample chamber have sedimented within the sample chamber before acquiring one or more microscopic images, calibrating the measurements.

[0052] In some applications, preparing a blood sample for analysis further includes staining the blood sample with one or more dyes, and calibration measurements include calibration measurements to account for the amount of staining experienced by entities within the blood sample prior to obtaining one or more microscopic images, the amount of staining being indicated by red blood cells that have settled within the sample chamber by more than a threshold amount.

[0053] Some applications in accordance with the present invention also provide a method including:

[0054] Placing a portion of a blood sample within a sample chamber;

[0055] Obtaining a microscopic image of red blood cells within the blood sample while the red blood cells within the blood sample are settling within the sample chamber;

[0056] Determining settling-dynamics characteristics of the blood sample by analyzing the image; and

[0057] Generating an output in response thereto.

[0058] In some applications, placing a portion of a blood sample within a sample chamber includes placing an undiluted portion of the blood sample within the sample chamber, and obtaining a microscopic image of red blood cells within the blood sample includes obtaining a microscopic image of red blood cells within the undiluted blood sample.

[0059] In some applications, determining settling-dynamics characteristics of the blood sample by analyzing the image includes determining settling-dynamics characteristics of the blood sample in real time relative to the settling of red blood cells within the blood sample.

[0060] In some applications, determining settling-dynamics characteristics of the blood sample by analyzing the image includes determining settling-dynamics characteristics of the blood sample while red blood cells within the blood sample are still settling.

[0061] In some applications, determining settling-dynamics characteristics of the blood sample by analyzing the image includes determining the settling rate of red blood cells within the blood sample by analyzing the image.

[0062] Some applications in accordance with the present invention also provide a method including:

[0063] Placing a first portion of a blood sample within a first sample chamber;

[0064] Placing a second portion of the blood sample within a second sample chamber;

[0065] Obtaining a microscopic image of the first portion of the blood sample;

[0066] Performing an optical density measurement on the second portion of the blood sample;

[0067] Detect that the concentration of a given entity in a test sample exceeds a threshold; and

[0068] Determine the reason for the concentration of the given entity exceeding the threshold by comparing the parameters determined from a microscopic image of a first portion of the blood sample with the parameters determined from an optical density measurement performed on a second portion of the blood sample.

[0069] In some applications, determining the reason for the concentration of the given entity exceeding the threshold includes determining that the blood sample itself is the reason for the concentration of the given entity in the sample exceeding the threshold by determining that the concentration of the entity indicated by the microscopic image is similar to the concentration of the entity determined by the optical density measurement.

[0070] In some applications, determining the reason for the concentration of the given entity exceeding the threshold includes determining that the preparation of one of the portions of the blood sample is the reason for the concentration of the given entity in the sample exceeding the threshold by determining that the concentration of the entity indicated by the microscopic image is different from the concentration of the entity determined by the optical density measurement.

[0071] Some applications according to the present invention also provide a method, including:

[0072] Place at least a portion of the blood sample in a sample chamber;

[0073] Obtain a microscopic image of a portion of the blood sample;

[0074] Identify at least one type of entity in the microscopic image selected from the group consisting of acanthocytes, spherocytes, and crenated erythrocytes;

[0075] Measure the count of the selected type of entity; and

[0076] Generate an output in response thereto.

[0077] In some applications, identifying at least one type of entity includes identifying acanthocytes. In some applications, identifying at least one type of entity includes identifying spherocytes. In some applications, identifying at least one type of entity includes identifying crenated erythrocytes.

[0078] In some applications, generating the output includes invalidating at least that portion of the blood sample from being used for performing at least some measurements on the blood sample, at least in part based on the count of the selected type of entity exceeding a threshold. In some applications, generating the output includes generating an indication of the count to the user. In some applications, generating the output includes generating an indication of the age of a portion of the sample to the user.

[0079] Some applications according to the present invention also provide a method, including:

[0080] Place at least a portion of the blood sample in a sample chamber;

[0081] Obtain a microscopic image of a portion of a blood sample;

[0082] Identify within the microscopic image at least one type of entity selected from the group consisting of acanthocytes, spherocytes, and crenated red blood cells;

[0083] Measure the count of the selected type of entity; and

[0084] Determine an indication of the aging of a portion of the sample, at least in part based on the count.

[0085] In some applications, the method further includes measuring a parameter of the sample by analyzing the microscopic image, and measuring the parameter of the sample includes performing measurements on the microscopic image and calibrating the measurements based on the determined indication of the lifespan of a portion of the sample.

[0086] In some applications, the method further includes measuring a parameter of the sample by performing an optical density measurement on a second portion of the blood sample, and measuring the parameter of the sample includes calibrating the optical density measurement based on the determined indication of the aging of a portion of the sample.

[0087] In some applications, identifying at least one type of entity includes identifying acanthocytes. In some applications, identifying at least one type of entity includes identifying spherocytes. In some applications, identifying at least one type of entity includes identifying crenated red blood cells.

[0088] Some applications according to the present invention also provide a method including:

[0089] Place at least a portion of a blood sample in a sample chamber, the sample chamber being a chamber including a substrate surface;

[0090] Cause the cells in the cell suspension to settle on the substrate surface of a carrier to form a monolayer of cells on the substrate surface of the carrier;

[0091] Obtain at least one microscopic image of at least a portion of the monolayer of cells;

[0092] Identify hemolyzed red blood cells within the microscopic image;

[0093] Measure the count of the identified hemolyzed red blood cells; and

[0094] Generate an output based on the count of the identified hemolyzed red blood cells.

[0095] In some applications, the method further includes estimating the total count of hemolyzed red blood cells in the blood sample that is greater than the count of the identified hemolyzed red blood cells, based on the count of the identified hemolyzed red blood cells, and generating the output includes generating an indication of the estimated total count of hemolyzed red blood cells to a user.

[0096] In some applications, generating an output includes invalidating at least a portion of the sample from being used to perform at least some measurements on the sample, at least in part based on a count of identified hemolyzed red blood cells exceeding a threshold.

[0097] In some applications, invalidating the sample from being used to perform at least some measurements on the sample includes: estimating a total count of hemolyzed red blood cells in the sample that is greater than the count of identified hemolyzed red blood cells, based on the count of identified hemolyzed red blood cells.

[0098] In some applications, the method further includes staining a blood sample, and identifying at least partially hemolyzed red blood cells includes distinguishing hemolyzed red blood cells from non-hemolyzed red blood cells by identifying red blood cells stained as hemolyzed by a stain.

[0099] In some applications, staining the blood sample includes staining the blood sample with a Hoechst reagent.

[0100] In some applications, obtaining at least one microscopic image of at least a portion of a monolayer of cells includes obtaining at least one bright-field microscopic image of at least a portion of a monolayer of cells, and identifying red blood cells stained by a stain includes identifying red blood cells having a contour visible in the bright-field microscopic image and having an interior similar to the background of the bright-field microscopic image.

[0101] In some applications, obtaining at least one microscopic image of at least a portion of a monolayer of cells includes obtaining at least one fluorescence microscopic image of at least a portion of a monolayer of cells, and identifying red blood cells stained by a stain includes identifying red blood cells that appear as bright circles in the image.

[0102] Some applications in accordance with the present invention also provide a method including:

[0103] Placing a biological sample in a sample chamber having a plurality of regions, each region defining a respective different height;

[0104] Measuring a parameter indicative of light transmission through the sample chamber at each region; and

[0105] Using a computer processor:

[0106] Normalizing the parameters measured at each region relative to one another;

[0107] Detecting, at least in part in response thereto, the presence of a bubble in the sample chamber; and

[0108] Performing an action in response to detecting the presence of a bubble in the sample chamber.

[0109] Some applications in accordance with the present invention additionally provide a method including:

[0110] Place a blood sample in a sample chamber having a plurality of regions, each region defining a respective different height;

[0111] Measure a parameter indicative of light transmission through the sample chamber at each region; and

[0112] Use a computer processor:

[0113] Calculate the hemoglobin concentration within the sample based on the absolute value of the parameter at the selected region;

[0114] Normalize the parameters measured at each region relative to each other; and

[0115] Validate the calculated hemoglobin concentration based on the normalized parameters.

[0116] Some applications according to the present invention also provide a method, including:

[0117] Place at least a portion of a blood sample within a sample chamber;

[0118] Obtain a microscopic image of a portion of the blood sample;

[0119] Identify candidates for a given entity within the blood sample in the microscopic image;

[0120] Verify at least some of the candidates as the given entity by performing further analysis on the candidates;

[0121] Compare the count of candidates for the given entity with the count of verified candidates for the given entity; and

[0122] Render at least a portion of the sample invalid for use in performing at least some measurements on the sample, at least in part based on the relationship between the count of candidates and the count of verified candidates.

[0123] In some applications:

[0124] Identifying candidates for a given entity within the blood sample in the microscopic image includes identifying platelet candidates within the blood sample in the microscopic image;

[0125] Verifying at least some of the candidates as the given entity by performing further analysis on the candidates includes: verifying at least some platelet candidates as platelets by performing further analysis on the candidates; and

[0126] Rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample includes: rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample, at least in part based on the relationship between the count of platelet candidates and the count of verified platelet candidates.

[0127] In some applications:

[0128] Identifying candidates for a given entity within a blood sample in a microscopic image includes identifying candidate white blood cells within the blood sample in the microscopic image;

[0129] Verifying at least some of the candidates as the given entity by further analyzing the candidates includes: verifying at least some of the candidate white blood cells as white blood cells by further analyzing the candidates; and

[0130] Rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample includes: rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample based at least in part on a relationship between a count of candidate white blood cells and a count of verified candidate white blood cells.

[0131] In some applications, rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample includes: rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample based on a ratio of the count of verified candidates to the count of candidates exceeding a maximum threshold.

[0132] In some applications, rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample includes: rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample based on a ratio of the count of verified candidates to the count of candidates being less than a minimum threshold.

[0133] Some applications according to the present invention also provide a method, including:

[0134] Placing at least a portion of a blood sample within a sample chamber;

[0135] Obtaining a microscopic image of a portion of the blood sample;

[0136] Identifying candidate white blood cells within the blood sample in the microscopic image;

[0137] Verifying at least some of the candidate white blood cells as white blood cells of a given type by further analyzing the candidate white blood cells;

[0138] Comparing the count of candidate white blood cells with the count of candidate white blood cells verified as white blood cells of a given type; and

[0139] Rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample based at least in part on a relationship between the count of candidate white blood cells and the count of candidate white blood cells verified as white blood cells of a given type.

[0140] Some applications according to the present invention also provide a method, including:

[0141] Stain a blood sample with one or more dyes;

[0142] Obtain at least one microscopic image of the blood sample;

[0143] Identify contaminants within the sample by identifying stained objects having irregular shapes;

[0144] Count one or more entities disposed within the sample by performing microscopic analysis on the sample; and

[0145] Invalidate a region of the sample disposed within a given distance of the identified contaminants such that it is not included in the count.

[0146] In some applications, staining a blood sample with one or more dyes includes staining the blood sample with acridine orange and a Hoechst reagent, and identifying debris includes identifying stained objects having irregular shapes and stained with both acridine orange and the Hoechst reagent.

[0147] Some applications according to the present invention also provide a method including:

[0148] Place at least a portion of the blood sample within a sample chamber;

[0149] Perform an optical measurement on the sample;

[0150] Based on the optical measurement, determine that one or more air bubbles are present within the sample chamber;

[0151] Generate an output based at least in part on determining that one or more air bubbles are present within the sample chamber.

[0152] In some applications, the method further includes determining one or more parameters of the sample based on the optical measurement, and invalidating at least some of the optical measurements such that they are not used to determine one or more parameters of the sample based on determining that one or more air bubbles are present within the chamber.

[0153] In some applications, generating an output includes invalidating a portion of the blood sample such that it is not used to perform at least some measurements on the sample based on determining that one or more air bubbles are present within the sample chamber.

[0154] In some applications, determining that one or more air bubbles are present within the sample chamber includes analyzing the light absorption distribution of the sample along a given direction of the sample chamber.

[0155] In some applications, performing an optical measurement on a sample includes performing one or more light absorption measurements at wavelengths at which hemoglobin does not absorb light, and determining the presence of one or more air bubbles in a sample chamber includes analyzing one or more light absorption measurements at wavelengths at which hemoglobin does not absorb light.

[0156] Some applications in accordance with the present invention also provide a method including:

[0157] Placing at least a portion of a blood sample in a sample chamber, the sample chamber being a chamber including a substrate surface;

[0158] Causing cells in a cell suspension to settle on a substrate surface of a carrier to form a monolayer of cells on the substrate surface of the carrier;

[0159] Obtaining at least one microscopic image of at least a portion of the monolayer of cells;

[0160] Identifying regions within the microscopic image where there is no sample; and

[0161] Invalidating at least the identified regions from being used for microscopic analysis of a portion of the sample.

[0162] In some applications, identifying regions where there is no sample includes identifying an interface between a wet region and a dry region on a substrate surface of the sample chamber.

[0163] In some applications, identifying regions where there is no sample includes differentiating regions where there is no sample from one or more regions where there is sample and the sample has a low cell density.

[0164] Some applications in accordance with the present invention also provide a method including:

[0165] Placing at least a portion of a blood sample in a sample chamber, the sample chamber being a chamber including a substrate surface and a top cover;

[0166] Causing cells in a cell suspension to settle on a substrate surface of a carrier to form a monolayer of cells on the substrate surface of the carrier;

[0167] When a microscope is focused on a monolayer focal plane, obtaining at least one microscopic image of at least a portion of the monolayer of cells, with a portion of the monolayer of cells being disposed within the monolayer focal plane;

[0168] Identifying dirt disposed on the top cover or on a lower side of the substrate surface by identifying regions where an entity is visible at a focal plane different from the monolayer focal plane; and

[0169] Invalidating at least the identified regions from being used for microscopic analysis of a portion of the sample.

[0170] Some applications in accordance with the present invention also provide a method, comprising:

[0171] Placing at least a portion of a blood sample in a sample chamber, the sample chamber being a chamber comprising a substrate surface and a top cover;

[0172] Causing cells in a cell suspension to settle on the substrate surface of a carrier to form a monolayer of cells on the substrate surface of the carrier;

[0173] When a microscope is focused on the monolayer focal plane, obtaining at least one microscope image of at least a portion of the monolayer of cells, a portion of the monolayer of cells being disposed within the monolayer focal plane;

[0174] Identifying regions in the microscope image where the background intensity indicates that fouling is disposed on the top cover or the underside of the substrate surface; and

[0175] Invalidating at least the identified regions from being used for microscopic analysis of a portion of the sample.

[0176] Some applications in accordance with the present invention also provide a method, comprising:

[0177] Staining at least a portion of a blood sample with a fluorescent dye;

[0178] Identifying stained cells within the blood sample by illuminating a portion of the sample with a light source that emits light in a given spectral band and obtaining a plurality of fluorescence microscope images of a portion of the blood sample by using a microscopic unit;

[0179] Identifying one or more fluorescent regions visible in the microscopic image obtained under illumination by the light source in addition to the stained cells; and

[0180] Determining the characteristics of the light source based on the identified fluorescent regions.

[0181] In some applications, determining the characteristics of the light source based on the identified fluorescent regions includes determining whether the spatial distribution of the illumination of the fluorescent light source has changed since the previous measurement.

[0182] In some applications, determining the characteristics of the light source based on the identified fluorescent regions includes determining whether the spatial uniformity of the illumination of the fluorescent light source has changed since the previous measurement.

[0183] In some applications, determining the characteristics of the light source based on the identified fluorescent regions includes determining whether the spatial position of the illumination of the fluorescent light source has changed since the previous measurement.

[0184] In some applications, determining the characteristics of the light source based on the identified fluorescent regions includes determining whether the vignette effect of the illumination of the fluorescent light source has changed since the previous measurement.

[0185] In some applications, determining the characteristics of a light source based on the identified fluorescent regions includes determining whether the spectral distribution of the illumination of the fluorescent light source has changed since the previous measurement.

[0186] In some applications, determining the characteristics of a light source based on the identified fluorescent regions includes determining whether the intensity of the illumination of the fluorescent light source has changed since the previous measurement.

[0187] In some applications, the method further includes determining a parameter of a blood sample by performing measurements on the stained cells and normalizing the measurements based on the determined light source characteristics.

[0188] In some applications, the method further includes invalidating at least some of the measurements based on the determined light source characteristics without performing them on the blood sample.

[0189] In some applications, identifying one or more fluorescent regions visible in a microscopic image obtained under illumination by a light source, other than the stained cells, includes identifying intercellular regions within the blood sample.

[0190] In some applications, identifying one or more fluorescent regions visible in a microscopic image obtained under illumination by a light source, other than the stained cells, includes identifying one or more fluorescent regions of a microscopic unit.

[0191] In some applications, obtaining a plurality of fluorescence microscope images of a portion of a blood sample includes: when the blood sample is contained in a sample carrier, obtaining a plurality of fluorescence microscope images of a portion of the blood sample, and identifying one or more fluorescent regions visible in the microscopic image obtained under illumination by the light source, other than the stained cells, includes identifying one or more fluorescent regions of the sample carrier.

[0192] In some applications, the sample carrier includes a glass and a plastic layer, the glass and the plastic layer being coupled to each other via a fluorescent pressure-sensitive adhesive, and identifying one or more fluorescent regions visible in the microscopic image obtained under illumination by the light source, other than the stained cells, includes identifying the pressure-sensitive adhesive.

[0193] Some applications according to the present invention also provide a method, including:

[0194] Staining at least a portion of a blood sample with a fluorescent dye;

[0195] Identifying the stained cells within the blood sample by illuminating a portion of the sample with a light source that emits light in a given spectral band and obtaining a plurality of fluorescence microscope images of the portion of the blood sample.

[0196] Identify one or more fluorescent regions visible in a microscopic image obtained under illumination by a light source, other than stained cells; and

[0197] Normalize the fluorescence of the stained cells based on the identified fluorescent regions.

[0198] In some applications, identifying one or more fluorescent regions visible in a microscopic image obtained under illumination by a light source, other than stained cells, includes identifying intercellular regions within a blood sample.

[0199] In some applications, identifying one or more fluorescent regions visible in a microscopic image obtained under illumination by a light source, other than stained cells, includes identifying one or more fluorescent regions of a microscopic unit.

[0200] In some applications, obtaining a plurality of fluorescence microscope images of a portion of a blood sample includes: obtaining a plurality of fluorescence microscope images of a portion of the blood sample when the blood sample is contained in a sample carrier, and identifying one or more fluorescent regions visible in a microscopic image obtained under illumination by a light source, other than stained cells, includes identifying one or more fluorescent regions of the sample carrier.

[0201] In some applications, the sample carrier includes a glass and a plastic layer, the glass and the plastic layer being coupled to each other via a fluorescent pressure-sensitive adhesive, and identifying one or more fluorescent regions visible in a microscopic image obtained under illumination by a light source, other than stained cells, includes identifying the pressure-sensitive adhesive.

[0202] Some applications according to the present invention also provide a method, including:

[0203] Identify entities within a blood sample by illuminating a portion of the blood sample with light from a bright-field light source and obtaining a plurality of bright-field microscope images of at least a portion of the blood sample;

[0204] Analyze the bright-field region of the light emitted by the bright-field light source in the absence of the blood sample; and

[0205] Determine the characteristics of the bright-field light source based on the analysis of the bright-field region of the light.

[0206] In some applications, determining the characteristics of the light source based on the identified bright-field region includes determining whether the spatial distribution of the illumination of the bright-field light source has changed since the previous measurement.

[0207] In some applications, determining the characteristics of the light source includes determining whether the spatial uniformity of the illumination of the bright-field light source has changed since the previous measurement.

[0208] In some applications, determining the characteristics of a light source includes determining whether the spatial position of the illumination of a bright-field light source has changed since the previous measurement.

[0209] In some applications, determining the characteristics of a light source includes determining whether the vignetting effect of the illumination of a bright-field light source has changed since the previous measurement.

[0210] In some applications, determining the characteristics of a light source includes determining whether the spectral distribution of the illumination of a bright-field light source has changed since the previous measurement.

[0211] In some applications, determining the characteristics of a light source includes determining whether the intensity of the illumination of a bright-field light source has changed since the previous measurement.

[0212] In some applications, analyzing the bright-field region of light emitted by a bright-field light source in the absence of a blood sample includes periodically analyzing the bright-field region of light emitted by the bright-field light source at fixed time intervals in the absence of a blood sample.

[0213] In some applications, analyzing the bright-field region of light emitted by a bright-field light source in the absence of a blood sample includes analyzing the bright-field region of light emitted by the bright-field light source after imaging a given number of blood samples using the bright-field light source.

[0214] In some applications, the method further includes determining a parameter of a blood sample by performing measurements on entities within the blood sample and normalizing the measurements based on the determined bright-field light source characteristics.

[0215] In some applications, the method further includes invalidating at least some measurements from being performed on the blood sample based on the determined bright-field light source characteristics.

[0216] Some applications according to the present invention also provide a method, including:

[0217] Staining portions of respective blood samples with at least one type of fluorescent dye;

[0218] Using a microscopic unit to obtain fluorescence microscopic images of portions of respective blood samples by illuminating a portion of the sample with a plurality of light sources, each of the plurality of light sources emitting light in a respective spectral band;

[0219] Detecting the presence of an error in at least some of the microscopic images; and

[0220] Classifying the source of the error as follows:

[0221] In response to detecting that the error was introduced from a given time point, identifying the fluorescent dye as the source of the error;

[0222] In response to detecting that the error gradually increases over time, the dirt within the microscopic unit is identified as the source of the error; and

[0223] In response to detecting that the error exists only in the image obtained under a given illumination from the light source, the given one in the light source is identified as the source of the error.

[0224] The present invention will be more fully understood from the following detailed description of embodiments of the present invention taken in conjunction with the accompanying drawings, in which: Brief Description of the Drawings

[0226] Figure 1 is a block diagram showing components of a biological sample analysis system according to some applications of the present invention;

[0227] Figure 2A 、 Figure 2B and Figure 2C are schematic diagrams of respective views of a sample carrier for performing both microscopic measurement and optical density measurement according to some applications of the present invention;

[0228] Figure 3A 、 Figure 3B and Figure 3C are microscopic images of a blood sample containing hemolyzed red blood cells obtained according to some applications of the present invention; and

[0229] Figure 4 is a graph showing the distribution of normalized light transmission intensity recorded along the length of a sample chamber according to some applications of the present invention. Detailed Description of Specific Embodiments

[0230] Now referring to Figure 1 , Figure 1 is a block diagram showing components of a biological sample analysis system 20 according to some applications of the present invention. Generally, a biological sample (e.g., a blood sample) is placed into a sample carrier 22. When the sample is placed in the sample carrier, optical measurements are performed on the sample using one or more optical measurement devices 24. For example, the optical measurement devices can include microscopes (e.g., digital microscopes), spectrophotometers, photometers, spectrometers, cameras, spectral cameras, hyperspectral cameras, fluorometers, spectrofluorometers, and / or photodetectors (such as photodiodes, photoresistors, and / or phototransistors). For some applications, the optical measurement devices include dedicated light sources (such as light-emitting diodes, incandescent light sources, etc.) and / or optical elements (such as lenses, diffusers, filters, etc.) for manipulating light collection and / or light emission. For some applications, the microscope system used is generally similar to the microscope system described by Greenfield in US 2014 / 0347459, which is incorporated herein by reference.

[0231] The computer processor 28 typically receives and processes the results of optical measurements performed by an optical measurement device. Additionally typically, the computer processor controls the acquisition of optical measurements performed by one or more optical measurement devices. The computer processor communicates with the memory 30. A user (e.g., a laboratory technician or an individual from whom a sample is drawn) sends instructions to the computer processor via the user interface 32. For some applications, the user interface includes a keyboard, a mouse, a joystick, a touchscreen device (such as a smartphone or a tablet computer), a touchpad, a trackball, a voice command interface, and / or other types of user interfaces known in the art. Typically, the computer processor generates an output via the output device 34. Additionally typically, the output device includes a display, such as a monitor, and the output includes the output displayed on the display. For some applications, the processor generates an output on different types of visual, text, graphic, tactile, audio, and / or video output devices (e.g., speakers, headphones, smartphones, or tablet computers). For some applications, the user interface 32 serves as both an input interface and an output interface, i.e., it serves as an input / output interface. For some applications, the processor generates an output on a computer-readable medium (e.g., a non-transitory computer-readable medium) such as a disk or a portable USB drive, and / or generates an output on a printer.

[0232] For some applications, the optical measurement device 24 (and / or the computer processor 28 and the memory 30) is housed within the optical measurement unit 31. To perform an optical measurement on a sample, the sample carrier 22 is placed within the optical measurement unit. Typically, the optical measurement unit includes a microscope system that is configured to perform microscopy imaging on a portion of the sample. For some applications, the microscope system includes a set of bright-field light sources (e.g., light-emitting diodes) configured for bright-field imaging of the sample, a set of fluorescence light sources (e.g., light-emitting diodes) configured for fluorescence imaging of the sample, and a camera (e.g., a CCD camera or a CMOS camera) configured to image the sample. Typically, the optical measurement unit also includes an optical density measurement unit that is configured to perform an optical density measurement (e.g., an optical absorption measurement) on a second portion of the sample. For some applications, the optical density measurement unit includes a set of optical density measurement light sources (e.g., light-emitting diodes) and a light detector that are configured to perform an optical density measurement on the sample. For some applications, each of the above-mentioned sets of light sources (i.e., a set of bright-field light sources, a set of fluorescence light sources, and a set of optical density measurement light sources) includes a plurality of light sources (e.g., a plurality of light-emitting diodes), each light source being configured to emit light at a corresponding wavelength or corresponding wavelength band.

[0233] Now refer to Figure 2A and Figure 2B , which are schematic views of respective views of the sample carrier 22 according to some applications of the present invention.Figure 2A shows a top view of the sample carrier (for illustrative purposes, the top lid of the sample carrier is shown as opaque in Figure 2A ), and Figure 2B shows a bottom view (where the sample carrier has been rotated about its short side relative to the Figure 2A view shown). Generally, the sample carrier includes a first set 52 of one or more chambers for microscopic analysis of a sample, and the sample carrier includes a second set 54 of one or more chambers for spectrophotometric measurement of a sample. Generally, the chambers of the sample carrier are filled with a body sample, such as blood, via a sample inlet hole 38. For some applications, the chambers define one or more outlet holes 40. The outlet holes are configured to facilitate filling of the chambers with the body sample by allowing air present in the chambers to be released from the chambers. Generally, as shown, the outlet holes are positioned longitudinally relative to the inlet holes (relative to the sample chambers of the sample carrier). For some applications, the outlet holes thus provide a more efficient air escape mechanism than if the outlet holes were positioned closer to the inlet holes.

[0234] Referring to Figure 2C , which shows an exploded view of a sample carrier 22 according to some applications of the present invention. For some applications, the sample carrier includes at least three components: a molded component 42, a glass plate 44, and an adhesive layer 46 configured to adhere the glass plate to the underside of the molded component. The molded component is typically made of a polymer (e.g., plastic) which is molded (e.g., via injection molding) to provide chambers having a desired geometry. For example, as shown, the molded component is typically molded to define an inlet hole 38, an outlet hole 40, and a gutter 48 around a central portion of each chamber. The gutter typically facilitates filling of the chambers with the body sample by allowing air to flow to the outlet hole and / or by allowing the body sample to flow around the central portion of the chamber.

[0235] For some applications, as Figure 2AThe sample carrier shown in -C is used in performing a complete blood count on a blood sample. For some applications, a first portion of the blood sample is placed within the chambers of the first set 52 (which are for microscopic analysis of the sample), and a second portion of the blood sample is placed within the chambers of the second set 54 (which are for performing spectrophotometric measurements on the sample). For some applications, the chambers of the first set 52 include multiple chambers, while the chambers of the second set 54 include only a single chamber, as shown. However, the scope of the present application includes using any number of chambers (e.g., a single chamber or multiple chambers) within the chambers of the first set or within the chambers of the second set or any combination thereof. The first portion of the blood sample is typically diluted relative to the second portion of the blood sample. For example, the diluent can contain a pH buffer, a stain, a fluorescent stain, an antibody, sphering agents, a lysing agent, etc. Typically, the second portion of the blood sample placed within the chambers of the second set 54 is a natural, undiluted blood sample. Alternatively or additionally, the second portion of the blood sample can be a sample that has been modified in some way, including, for example, dilution (e.g., diluted in a controlled manner), addition of a component or reagent, or fractionation, or one or more of these.

[0236] For some applications, prior to performing microscopic imaging of the sample, the first portion of the blood sample (which is placed within the chambers of the first set 52) is stained using one or more staining substances. For example, the staining substance can be configured to stain DNA preferentially over staining other cellular components. Alternatively, the staining substance can be configured to stain all cellular nucleic acids preferentially over staining other cellular components. For example, the sample can be stained with an acridine orange reagent, a Hoechst reagent, and / or any other staining substance configured to preferentially stain DNA and / or RNA within the blood sample. Optionally, the staining substance is configured to stain all cellular nucleic acids, but the staining of DNA and RNA is each more visibly prominent under some illumination and filtering conditions, as is known, for example, with respect to acridine orange. Images of the sample can be acquired using imaging conditions that permit detection of the cells (e.g., bright field) and / or imaging conditions that permit visualization of the stained bodies (e.g., appropriate fluorescent illumination). Typically, the first portion of the sample is stained with acridine orange and with a Hoechst reagent. For example, the first (diluted) portion of the blood sample can be prepared using techniques such as those described in Pollak's US 2015 / 0316477, which is incorporated herein by reference and describes a method for preparing a blood sample for analysis that involves a dilution step that facilitates the identification and / or counting of components in a microscopic image of the sample.

[0237] Typically, prior to microscopic imaging, the first portion of blood (placed in the chambers of the first set 52) is allowed to sediment, such as forming a monolayer of cells using the techniques described in Pollak's US 9,329,129, which is incorporated herein by reference. For some applications, microscopic analysis of the first portion of the blood sample is performed with respect to the monolayer of cells. Typically, the first portion of the blood sample is imaged under bright field imaging, i.e., under illumination from one or more light sources (e.g., one or more light emitting diodes, which typically emit light at respective spectral bands). Additionally, typically, the first portion of the blood sample is further imaged under fluorescence imaging. Typically, fluorescence imaging is performed by directing light at a known excitation wavelength (i.e., wavelengths at which the stained objects in the sample are known to emit fluorescence if excited by light at these wavelengths) to excite the stained objects (i.e., objects that have absorbed the dye) within the sample, and detecting the fluorescence. Typically, for fluorescence imaging, a separate set of light sources (e.g., one or more light emitting diodes) is used to illuminate the sample at a known excitation wavelength.

[0238] Note that in the context of the present application, the term monolayer is used to denote a layer of cells that has sedimented, such as being disposed within a single focal field of a microscope. Some overlap of cells may be present within the monolayer such that two or more overlapping layers of cells are present in certain regions. For example, red blood cells may overlap each other within the monolayer, and / or platelets may overlap the red blood cells within the monolayer, or be disposed above them.

[0239] As described in Pollack's US 2019 / 0302099, which is incorporated herein by reference, for some applications, chambers belonging to group 52 (which are used for microscopic measurements) have different heights from each other to facilitate the measurement of different measurands using microscope images of the respective chambers, and / or different chambers are used for microscopic analysis of respective sample types. For example, if a blood sample and / or a monolayer formed from the sample has a relatively low density of red blood cells, measurements can be performed within a chamber of a sample carrier having a greater height (i.e., a chamber of a sample carrier having a greater height relative to different chambers having a relatively lower height), such that there is a sufficient density of cells, and / or such that there is a sufficient density of cells within a monolayer formed from the sample, to provide statistically reliable data. Such measurements can include, for example, red blood cell density measurement, measurement of other cell properties (such as counting of abnormal red blood cells, red blood cells including endosomes (e.g., pathogens, chromatosomes), etc.), and / or hemoglobin concentration. Conversely, if a blood sample and / or a monolayer formed from the sample has a relatively high density of red blood cells, such measurements can be performed on a chamber of a sample carrier having a relatively low height, e.g., such that there are sufficiently sparse cells, and / or such that there are sufficiently sparse cells within a monolayer of cells formed from the sample, so that cells can be identified in a microscopic image. For some applications, such methods can be performed even if there is no precisely known height variation between chambers belonging to group 52.

[0240] For some applications, depending on the measurand being measured, a chamber for performing an optical measurement within a sample carrier is selected. For example, a chamber of a sample carrier having a greater height can be used to perform white blood cell counting (e.g., to reduce statistical errors that may result from low counts in a shallower region), white blood cell differentiation, and / or detection of rarer forms of white blood cells. Conversely, to determine mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), red blood cell distribution width (RDW), red blood cell morphological features, and / or red blood cell abnormalities, microscopic images can be obtained from a chamber of a sample chamber having a relatively low height, because in such a chamber, cells are relatively sparsely distributed in a zone of the region, and / or a monolayer is formed in which cells are relatively sparsely distributed. Similarly, to perform platelet counting, platelet classification, and / or extract any other property of platelets (such as volume), microscopic images can be obtained from a chamber of a sample chamber having a relatively low height, because there are fewer red blood cells in such a chamber that overlap (fully or partially) with platelets in the microscopic image and / or in the monolayer.

[0241] According to the above example, preferably, a chamber with a sample carrier of lower height is used for optical measurement to measure some analytes in a sample (such as a blood sample), while a chamber with a sample carrier of higher height is preferably used for optical measurement to measure other analytes in the sample. Thus, for some applications, a first analyte in the sample is measured by performing a first optical measurement (e.g., by acquiring its microscopic image) on a portion of the sample disposed in a first chamber belonging to group 52 of the sample carrier, and a second analyte of the same sample is measured by performing a second optical measurement (e.g., by acquiring its microscopic image) on a portion of the sample disposed in a second chamber of group 52 of the sample carrier. For some applications, such as using the techniques described in Zait's US 2019 / 0145963, which is incorporated herein by reference, the first and second analytes are normalized relative to each other.

[0242] Generally, in order to perform an optical density measurement on a sample, it is desirable to know as precisely as possible the optical path length, volume, and / or thickness of the portion of the sample on which the optical measurement is performed. Generally, an optical density measurement is performed on a second portion of the sample, which is typically placed in an undiluted form in the chambers of the second group 54. For example, the concentration and / or density of a component can be measured by performing an optical absorption, transmission, fluorescence, and / or luminescence measurement on the sample.

[0243] Referring again to Figure 2A, for some applications, a chamber belonging to group 54 (which is used for optical density measurement) typically defines at least a first region 56 (which is typically deeper) and a second region 58 (which is typically shallower), and the height of the chamber varies between the first and second regions in a predefined manner, for example, as described in Pollack's WO 17 / 195205, which is incorporated herein by reference. The height of the first region 56 and the second region 58 of the sample chamber is defined by the lower surface defined by the glass plate and the upper surface defined by the molded part. The upper surface at the second region is stepped relative to the upper surface at the first region. The step between the upper surfaces at the first and second regions provides a predefined height difference Δh between the regions, such that even if the absolute heights of the regions are not known with sufficient precision (e.g., due to tolerances in the manufacturing process), the height difference Δh is known with sufficient precision to use the techniques described herein and as described in Pollack's US 2019 / 0302099, which is incorporated herein by reference, to determine the parameters of the sample. For some applications, the height of the chamber varies from the first region 56 to the second region 58, and then the height varies again from the second region to the third region 59, such that along the sample chamber, the first region 56 defines the maximum height region, the second region 58 defines the medium height region, and the third region 59 defines the minimum height region. For some applications, additional variations in height occur along the length of the chamber, and / or the height varies gradually along the length of the chamber.

[0244] As described above, when a sample is disposed in a sample carrier, one or more optical measurement devices 24 perform optical measurements on the sample. Generally, the optical measurement device observes the sample through a glass layer that is transparent at least to the wavelengths typically used by the optical measurement device. Generally, when performing optical measurements, the sample carrier is inserted into an optical measurement unit 31 that houses the optical measurement device. Generally, the optical measurement unit houses the sample carrier such that the molded layer is disposed above the glass layer and such that the optical measurement unit is disposed below the glass layer of the sample carrier and is capable of performing optical measurements on the sample through the glass layer. The sample carrier is formed by adhering a glass plate to a molded component. For example, the glass plate and the molded component may be joined to each other during manufacturing or assembly (e.g., using thermal bonding, solvent-assisted bonding, ultrasonic welding, laser welding, heat staking, adhesives, mechanical clamping, and / or an additional substrate). For some applications, the glass layer and the molded component are joined to each other using an adhesive layer 46 during manufacturing or assembly. For some applications, due to tolerances in the manufacturing process, the absolute height of the sample chamber is unknown. As described above, the step between the upper surfaces at the first and second regions provides a predefined height difference Δh between the regions such that even if the absolute height of the regions is not known with sufficient precision (e.g., due to tolerances in the manufacturing process), the height difference Δh is known with sufficient precision to determine parameters of the sample. For example, using the techniques described herein and as described in Pollack's US 2019 / 0302099, which is incorporated herein by reference, alternative or additional height variations along the length of the chamber (e.g., step variations in height or gradual variations in height) may be used as an alternative or addition to the step between the first and second regions.

[0245] For some applications, a portion of the sample carrier 22 is configured to fluoresce at least under certain conditions. For example, a portion of the sample carrier may be configured to fluoresce when exposed to light emitted by the optical measurement device 24 (e.g., brightfield light or fluorescence emitted by a microscope system). Or a portion of the sample carrier may be configured to fluoresce when placed within the optical measurement unit 31 that houses the optical measurement device 24. As described above, for some applications, the sample carrier 22 includes an adhesive layer 46. For some applications, the adhesive layer or a portion thereof is configured to fluoresce in the manner described above (e.g., through an adhesive material within the adhesive layer that is configured to fluoresce, through an adhesive layer containing an additional material configured to fluoresce, and / or through an adhesive layer coated with such a material). For some applications, the adhesive layer is a pressure-sensitive adhesive, at least a portion of which is configured to fluoresce. For example, the pressure-sensitive adhesive may be an acrylic-type pressure-sensitive adhesive, at least a portion of which is configured to fluoresce.

[0246] In some applications according to the present invention, various techniques are performed (usually by a computer processor) to determine whether various errors have occurred and, if so, optionally identify the source of the error. These errors may stem from the preparation of all samples. For example, before performing a measurement, the sample may have remained in the sample carrier for too long (which may cause sample degradation and / or which may cause the dye mixed with one or both parts of the sample to be overly absorbed by entities within the sample). Alternatively, the error may stem from the preparation of a particular part of the sample. For example, there may be an error in the preparation of the first part (which is typically diluted and placed in the chambers of the first set 52 for microscopic analysis), such as an error in diluting the first part of the sample, air bubbles entering the chambers of the first set 52, or contamination of this part of the sample. Alternatively or additionally, there may be an error in the preparation of the second part (which is typically undiluted and placed in the chambers of the second set 54 for analysis via optical density measurement), such as contamination of this part or air bubbles entering the chambers of the second set 54.

[0247] Alternatively or additionally, the error may stem from an error in the sample carrier (such as the material of the sample carrier itself (e.g., the substrate) being unclean, and / or dirt or spilled blood on the sample carrier), and / or an error in the microscope system itself, such as illumination (e.g., light-emitting diodes for bright-field imaging and / or light-emitting diodes used during fluorescence imaging of the sample), and / or an error associated with the optical path and / or motor and stage components or controller, and / or an error caused by the environment in which the device is placed (e.g., relative humidity, temperature, pressure, particle concentration, or any other environmental factor). Additionally, alternatively or additionally, there may be an inherent problem with the sample (such as a very low or very high count of a particular entity, or too much time having passed since sample collection was performed), which means that the computer processor cannot perform certain measurements with sufficient precision, and / or which means that the computer processor should flag this to the user.

[0248] For some applications, in response to identifying an error, the computer processor outputs a message indicating the error and / or indicating the source of the error. For some applications, the computer processor does not perform certain measurements on the blood sample in response to identifying an error. For some applications, in response to identifying an error, the computer processor does not perform any measurements on the sample, and / or flags the sample as invalid to the user, and / or instructs the user to repeat sample preparation with a new kit and / or recollect the blood sample. Alternatively or additionally, the computer processor determines certain parameters of the blood sample by calibrating the measurements performed on the blood sample in order to account for the error.

[0249] For some applications, for example, one or more of the following errors are accounted for in one or more of the above ways:

[0250] Errors in the microscopy device, such as:

[0251] - The out-of-step of the motor moving the microscope stage

[0252] - The recoil variation of the movement of the microscope stage (e.g., as described in further detail below)

[0253] - The timing variation between the microscope camera and the microscope stage (e.g., as described in further detail below)

[0254] - The alignment between the microscope camera and the microscope stage (e.g., due to the relative rotation between these components)

[0255] - Problems with the optical system (e.g., the change in focus quality over time, e.g., caused by the sample, or by a piece of the microscope stage (e.g., a scratched piece), e.g., as described in further detail below)

[0256] - The leveling variation in the microscope system

[0257] - The variation of the expected focus position along the z-axis (i.e., the optical axis)

[0258] - The loss of communication between components

[0259] - The variation of the linear response of the camera

[0260] Errors caused by environmental factors, such as:

[0261] - The device being outside the allowable temperature, humidity, altitude, etc.

[0262] - Specific components being outside the target values

[0263] General errors caused by the following factors:

[0264] - Scanning time

[0265] - Device startup time

[0266] - Available working / storage memory

[0267] Some examples of techniques for identifying errors and addressing such errors are described below.

[0268] As described above, generally, the first part of the blood sample is microscopically analyzed while being placed in the sample chambers of the first group 52. Generally, before microscopic imaging, the first part of the blood (which is placed in the chambers of the first group 52) is allowed to settle, such as using the techniques described in Pollak's US 9,329,129, which is incorporated herein by reference, to form a monolayer of cells.

[0269] For some applications, a computer processor is configured to determine whether one or more cell types (e.g., red blood cells) in a sample chamber have settled in the sample chamber before the sample carrier is placed in the microscopic unit by acquiring one or more microscopic images of the sample after the sample carrier is placed in the microscopic unit and analyzing the one or more images.

[0270] Typically, if it is determined that all red blood cells have settled before the microscopic image is acquired, this indicates that the blood sample has remained in the sample chamber for too long before the sample carrier is placed in the microscopic unit. It should be noted that although the analysis of the microscopic image is generally performed with respect to a single layer of settled cells, it is still desirable to place the sample carrier in the microscopic unit while some red blood cells are still settling, as this indicates that the sample has not remained in the sample carrier for too long before being placed in the microscopic unit. Conversely, if all red blood cells (or a large enough proportion of red blood cells) have settled, then the sample may have degraded and / or the stain may have been overly absorbed by entities within the sample. Thus, the degree to which cells are still settling can be used as a measure of the most recent time the sample was taken from the subject and / or the most recent time the sample was placed in the sample carrier or sample chamber (i.e., the freshness of the sample). Accordingly, for some applications, in response to determining that more than a threshold amount of red blood cells in the sample chamber have settled in the sample chamber before one or more microscopic images are acquired, the sample (or a portion thereof) is rendered invalid and not used for performing at least some measurements on the sample.

[0271] For some applications, an indication of the aging of a blood sample is determined at least in part based on determining whether one or more cell types in the sample chamber have settled in the sample chamber before one or more microscopic images are acquired. For some applications, an indication of the aging of a blood sample is determined at least in part based on the amount (or proportion) of one or more cell types in the sample chamber that have not settled in the sample chamber before one or more microscopic images are acquired.

[0272] For some applications, an analysis substantially similar to the analysis described in the above paragraph (for determining the most recent time the sample was taken from the subject and / or the most recent time the sample was placed in the sample carrier or sample chamber) is performed on a second portion of the sample (which is typically placed in the chambers of the second set 54 in undiluted form).

[0273] Note that, typically, after a computer processor (e.g., using the above-described analysis techniques) has determined an indication of the time of most recently extracting a sample from a subject and / or the time of most recently placing a sample in a sample carrier or sample chamber, the sample carrier is left in place within the microscopy unit for a few minutes (e.g., between 2 - 10 minutes, e.g., about 5 minutes) before further imaging of the first portion of the blood sample (for microscopic analysis of the blood sample). This is to allow the first portion of the blood sample time to settle into a monolayer.

[0274] For some applications, in response to determining that more than a threshold amount of red blood cells have settled within the sample chamber prior to acquiring one or more microscopic images, calibrate the measurements performed on the sample. For example, such measurements can be calibrated to account for the amount of staining experienced by entities within the blood sample prior to acquiring one or more microscopic images, as indicated by more than a threshold amount of red blood cells that have settled within the sample chamber. For some applications, prior to acquiring one or more microscopic images, calibrate the measurements performed on the sample based on the amount (or proportion) of one or more cell types that have not settled within the sample chamber.

[0275] For some applications, as red blood cells within the blood sample settle within the sample chamber, acquire microscopic images of the red blood cells within the blood sample and determine the sedimentation kinetic properties (e.g., red blood cell sedimentation rate) of the blood sample by a computer processor analyzing the images. Typically, the sedimentation kinetic properties (e.g., red blood cell sedimentation rate) of the blood sample are determined by the computer processor in real time relative to the sedimentation of the red blood cells (i.e., while the red blood cells are still settling). This is in stark contrast to other techniques for determining the sedimentation kinetic properties (e.g., red blood cell sedimentation rate) of a blood sample, where the total time required for the red blood cells to sediment is measured. Note that if such a measurement is performed on a diluted portion of the blood sample, the effect of proteins on the sedimentation time of the red blood cells is diminished. Thus, for some applications, such a measurement is performed on an undiluted portion of the blood sample.

[0276] For some applications, use per-sample information (such as mean cell volume of red blood cells or platelets, mean cell hemoglobin concentration, or other such sample indicative measurements) to correct the above-described determination of the indication of the time of most recently extracting a sample from a subject and / or the time of most recently placing a sample in a sample carrier and / or the analysis for determining the sedimentation kinetic properties. Alternatively or additionally, use information at the single-cell level (i.e., by extracting data related to individual cells and correcting the determined sedimentation kinetic properties based on this data) to correct the determination of the indication of the time of most recently extracting a sample from a subject and / or the time of most recently placing a sample in a sample carrier and / or the analysis for determining the sedimentation kinetic properties.

[0277] For some applications, in response to determining that the concentration of a given entity within a blood sample exceeds a threshold, a computer processor determines the reason that the concentration of the given entity exceeds the threshold by comparing parameters determined from a microscopic image of a first portion of the blood sample with parameters determined from an optical density measurement performed on a second portion of the blood sample. For example, in response to detecting that the first portion of the sample (which is typically diluted and placed in a chamber of the first set 52) has a very high red blood cell count or a very low red blood cell count, the computer processor may perform the comparison in order to determine whether it is the case that the blood sample inherently has a very high red blood cell count or a very low red blood cell count, or whether it is caused by an error in the preparation of that portion of the sample (e.g., dilution of the first portion). The computer processor generally determines that the blood sample itself is the reason that the concentration of the given entity within the sample exceeds the threshold by determining that the concentration of the entity indicated by the microscopic image is similar to the concentration of the entity determined by the optical density measurement. Also generally, the computer processor determines that the preparation of that portion of the blood sample is the reason that the concentration of the given entity within the sample exceeds the threshold by determining that the concentration of the entity indicated by the microscopic image is different from the concentration of the entity determined by the optical density measurement.

[0278] For some applications, a similar analysis as described in the previous paragraph is performed using sample parameters other than concentration (e.g., mean cell volume, mean cell hemoglobin, etc.). For some applications, in response to identifying a difference between parameters measured for corresponding portions of the sample, it is determined that the corresponding portions of the sample may be portions of two different samples (e.g., from two different patients).

[0279] For some applications, parameters determined from corresponding portions of a sample are used to correct each other. For example, if the values of a parameter measured in each sample portion are different from each other, but a third value (or range of values) within the error range of the two values of the parameter measured in each sample portion is determined to exist, then it can be determined that the third value (or range of values) may be correct.

[0280] For some applications, in response to one or more parameters of a sample being outside of a normal range, a computer processor compares these parameters with other parameters of the sample. In response to all parameters being outside of the normal range (or even being incorrect in a manner related to an error in one or more of the parameters), then the computer processor may determine that this is due to an error in the calculation affecting all of these parameters.

[0281] For some applications, a computer processor is configured to identify acanthocytes, spherocytes, and / or echinocytes within a microscopic image of a first portion of a sample. Generally, the presence of such entities is an indication that the portion of the sample has degraded due to aging and / or sample storage conditions. For some such applications, the computer processor measures the count of such entities and, at least in part based on the count of a selected type of entity exceeding a threshold, invalidates at least that portion of the blood sample from being used to perform at least some measurements on the blood sample. For some applications, the computer processor generates an indication of the count and / or an associated clinical condition to a user. Alternatively or additionally, the computer processor determines an indication of the aging of the sample portion at least in part based on the count. For some applications, to determine a parameter of the sample, measurements are performed on the microscopic image and the measurements are calibrated based on the determined indication of the aging of the sample portion and / or based on the count of the foregoing entities. For some applications, the parameter of the sample is determined by performing an optical density measurement on a second portion of the blood sample (which is typically disposed within a sample chamber of a second set 54) and calibrating the optical density measurement based on the determined indication of the aging of the sample portion and / or based on the count of the foregoing entities. (For some applications, the optical density measurement is calibrated based on one or more other factors such as red blood cell morphology, red blood cell volume, platelet count, level of debris within the sample, and / or the presence or amount of any object or property that may affect scattering.)

[0282] For some applications, the computer processor estimates the volume of acanthocytes, spherocytes, and / or echinocytes. For some such applications, the volume of these cells is incorporated into an overall measurement of the mean red blood cell volume within the sample.

[0283] Now refer to Figure 3A and Figure 3B , which are brightfield microscopic images obtained under purple and green LED illumination, respectively, for some applications of the present invention. As described above, a microscopic image of a first portion of a blood sample is typically acquired and a monolayer of cells within that first portion is analyzed. Generally, sphering techniques are not applied to red blood cells within the sample prior to imaging a portion of the sample. The inventors of the present application have found that when a portion of a sample is microscopically imaged using the techniques described herein, some hemolyzed red blood cells are visible in the microscopic image. Generally, after the sample is stained with a Hoechst reagent (or any fluorescent or non-fluorescent dye that has an affinity for cell membranes), the cell outline is visible under brightfield imaging, but the remainder of the cell appears as the background of the image. This effect can be observed in Figure 3A and Figure 3B where red blood cells 60 are visible and the outline of hemolyzed red blood cell 62 is visible, but the interior of the cell appears similar to the background such that the outline appears as an "empty" cell. "Empty" cells generally have a shape and size similar to that of red blood cells.

[0284] Also refer to Figure 3C which is a fluorescence microscopic image obtained according to some applications of the present invention. The image was recorded after a blood sample had been stained with Hoechst reagent and excited using UV irradiation centered at approximately 360 nm. It can be observed that, unlike red blood cells 60 which appear vaguely as dark circles, hemolyzed red blood cells 62 appear as bright circles having a shape and size roughly similar to those of red blood cells. It is speculated that the hemolyzed red blood cells are stained with the Hoechst reagent bound to residues remaining on the membrane of the hemolyzed red blood cells. This results in the hemolyzed red blood cells appearing as "empty" cells in the bright field image, and / or as bright circles in the fluorescence image. It is further hypothesized that the reason red blood cells appear as dark circles in the fluorescence image is because of the background radiation of free Hoechst reagent present throughout the sample, but this radiation is attenuated by hemoglobin in the red blood cells, making them appear darker than the background.

[0285] Thus, according to some applications of the present invention, hemolyzed red blood cells are identified within a non-spheroidized blood sample. Typically, the sample is stained with a dye such as Hoechst reagent (or any fluorescent or non-fluorescent dye having an affinity for cell membranes). The hemolyzed red blood cells are identified in the bright field image of the stained sample by identifying cells whose outline is visible, but whose interior appears roughly similar to the background (such that the outline looks like an "empty" cell). Alternatively or additionally, the hemolyzed red blood cells are identified within the fluorescence image of the stained sample. Typically, the hemolyzed red blood cells have a shape and size roughly similar to those of the red blood cells within the image.

[0286] For some applications, the visible hemolyzed red blood cells only constitute a small portion of the total number of hemolyzed red blood cells present within the sample portion, because typically, a portion of the hemolyzed red blood cells are not visible. For some applications, a computer processor identifies the visible hemolyzed red blood cells and measures the count of the identified hemolyzed red blood cells within a portion of the sample. Typically, based on the count of the identified hemolyzed red blood cells, the computer processor estimates the total count of hemolyzed red blood cells within the portion of the sample that is greater than the count of the identified hemolyzed red blood cells. Alternatively or additionally, based on the count of the identified hemolyzed red blood cells, the computer processor estimates the ratio of hemolyzed red blood cells to non-hemolyzed red blood cells within the sample. Typically, this ratio is calculated by estimating the total count of hemolyzed red blood cells within a portion of the sample that is greater than the count of the identified hemolyzed red blood cells. For some applications, the computer processor outputs an indication of the estimated total count of hemolyzed red blood cells or the ratio of hemolyzed red blood cells to non-hemolyzed red blood cells within the blood sample to the user. Alternatively or additionally, the computer processor invalidates the sample from being used to perform at least some measurements on the sample, at least in part, based on the count of the identified hemolyzed red blood cells exceeding a threshold, or based on the above ratio exceeding a threshold. For some applications, the invalidation of the sample is based on estimating the total count of hemolyzed red blood cells within a portion of the sample that is greater than the count of the identified hemolyzed red blood cells.

[0287] For some applications, to identify a given entity (such as platelets, red blood cells, white blood cells, etc.) within a blood sample, a computer processor first identifies candidates for the given entity within the blood sample by analyzing a microscopic image of a first portion of the blood sample. Subsequently, the computer processor validates at least some of the candidates as the given entity by performing further analysis on the candidates.

[0288] For some applications, a computer processor compares a count of candidates for a given entity with a count of verified candidates for the given entity and invalidates at least a portion of a sample from being used to perform at least some measurements on the sample, at least in part based on a relationship between the count of candidates and the count of verified candidates. For example, if a ratio of the count of verified candidates to the count of candidates exceeds a maximum threshold, the computer processor may invalidate at least a portion of the sample from being used to perform at least some measurements on the sample because this indicates that too many candidates are verified, suggesting an error. Alternatively or additionally, if the ratio of the count of verified candidates to the count of candidates is below a minimum threshold, the computer processor may invalidate at least a portion of the sample from being used to perform at least some measurements on the sample because this indicates that too few candidates are verified, suggesting an error. For some applications, if a ratio of the count of verified platelets to the count of platelet candidates is below a minimum threshold, the computer processor invalidates at least a portion of the sample from being used to perform a platelet count because this indicates that too few platelet candidates are verified as platelets, suggesting an error. For example, such an error may be caused by debris (or other contaminants) being misidentified as platelets or platelet candidates. Note that the source of the error may be in the preparation of the portion of the sample, in the sample carrier, in portions of the microscopic unit, and / or in the blood itself. For some applications, similar techniques are performed for red blood cells, white blood cells, and / or other entities (e.g., abnormal white blood cells, circulating tumor cells, red blood cells, reticulocytes, Howell-Jolly bodies, etc.) within the sample.

[0289] For some applications, a computer processor is configured to identify white blood cell candidates within a blood sample and then configured to verify at least some of the white blood cell candidates as white blood cells of a given type (e.g., neutrophils, lymphocytes, eosinophils, monocytes, blasts, immature cells, atypical lymphocytes, and / or basophils) by performing further analysis on the white blood cell candidates. For some applications, the computer processor compares the count of white blood cell candidates with the count of white blood cell candidates that are verified as white blood cells of a given type and, at least in part based on the relationship between the count of white blood cell candidates and the count of white blood cell candidates that are verified as white blood cells of a given type, invalidates at least a portion of the sample from being used to perform at least some measurements on the sample. For example, if the ratio of the count of white blood cell candidates that are verified as white blood cells of a given type to the count of white blood cell candidates exceeds a maximum threshold, the computer processor may invalidate at least a portion of the sample from being used to perform at least some measurements on the sample because this indicates that too many candidates have been verified, suggesting an error. Alternatively or additionally, if the ratio of the count of white blood cell candidates that are verified as white blood cells of a given type to the count of white blood cell candidates is below a minimum threshold, the computer processor may invalidate at least a portion of the sample from being used to perform at least some measurements on the sample because this indicates that too few candidates have been verified, suggesting an error. Note that the source of the error may be in the preparation of the portion of the sample, in the sample carrier, in parts of the microscopic unit, and / or in the blood itself.

[0290] For some applications, the computer processor is configured to identify debris (or other contaminants) within a sample by identifying stained objects having irregular shapes (e.g., fibrous shapes, non-circular shapes, and / or elongated shapes). As described above, typically, the computer processor performs a count of one or more entities disposed within the sample by performing microscopic analysis on the sample. For some applications, the computer processor invalidates sample regions disposed within a given distance of the identified debris (or other contaminants) from being included in the count. Typically, the debris is stained by a dye and, typically further, the debris is stained with acridine orange and a Hoechst reagent. For some applications, the computer processor identifies debris (or other contaminants) by identifying objects having irregular shapes and / or stained by a dye (e.g., acridine orange and a Hoechst reagent).

[0291] Now refer to Figure 4, which is a graph showing the normalized logarithm of the light transmission intensity measured along the length of the sample chamber belonging to the second set 54 for some applications of the present invention. As described above, generally, a computer processor is configured to perform optical measurements (e.g., optical density measurements) on a second portion of a sample placed in the sample chambers of the second set 54. For some applications, light (e.g., light from an LED) is transmitted through the chamber in the spectral band where hemoglobin absorbs light, and the intensity of the transmitted light is detected by a photodetector. According to the Beer-Lambert law, the amount of light absorbed is interpreted as indicating the concentration of hemoglobin in the second portion of the sample.

[0292] For some applications, the computer processor determines, based on the optical measurements, that one or more air bubbles are present in one of the sample chambers of the second set. For example, due to regions of different heights within the sample chamber, the normalized logarithm distribution of the transmission intensity along the length of the chamber (which is related to the hemoglobin absorption distribution) is expected to have a given shape, e.g., regions where the logarithm of the light transmission intensity is substantially constant as a result of the differences between the regions (due to the steps in the height of the chamber). This is represented by Figure 4 the solid line 70 in, which is a combination of the normalized logarithms of the transmission intensities recorded along the length of the sample chamber for several different samples. As shown, along the minimum height region 56 of the sample chamber, the logarithm of the transmission intensity is substantially constant. (In fact, there is a slight slope along the length of this region due to height variations along the length of this region resulting from tolerances in the manufacture of the sample carrier, as described above.) Then, as the distance along the sample chamber transitions to the medium height region 58 (where hemoglobin absorption is greater and thus light transmission is lower), the logarithm of the transmission intensity decreases, and then as the distance along the sample chamber transitions to the maximum height region 59 (where hemoglobin absorption is greater and thus light transmission is lower), the logarithm of the transmission intensity further decreases. Note that the way the transmission is normalized is by taking the average value of the logarithm of the light transmission intensity within a given portion of the maximum height region and assigning it the value 1, taking the average value of the logarithm of the light transmission intensity within a given portion of the minimum height region and assigning it a second value, and then normalizing the other values with respect to these two values. (In some cases, the value of the logarithm of the light transmission intensity within a given portion of the minimum height region is assigned the value of the Euler number (i.e., 2.718), although this is not the case in the Figure 4 example shown.) It is expected that the normalized distribution of any sample filling the sample chamber will have a similar distribution regardless of the absolute hemoglobin absorption rate of the sample, since the shape of the distribution depends on the relative absorption in different regions along the sample chamber.

[0293] Figure 4The thin curve 72 therein shows the normalized logarithm of the transmission intensity recorded along the length of the sample chamber for a given sample. It can be observed that within the minimum height region, there is a relatively flat portion of the curve (which is below curve 70), followed by a peak (which is above curve 70). Additionally, along the medium height region, curve 72 is below curve 70. Generally, such a distribution indicates the fact that there are bubbles (e.g., air bubbles and / or the presence of different substances) within the minimum height region. At the location of the bubbles, the light transmission is greater, resulting in a peak in curve 72 at that location. At other locations (e.g., within other parts of the minimum height region) and along the entire medium height region, the presence of bubbles within the minimum height region causes the normalized logarithmic value of the transmission intensity to decrease relative to the value of a sample without bubbles. Similarly, when there are bubbles within other regions (or along the entire region) of the sample chamber, this will result in a different distribution of the normalized logarithm of the transmission intensity. For example, if there are bubbles along the entire minimum height region, this will cause the normalized logarithm of the transmission intensity within the medium height region to decrease relative to the normalized logarithm of the transmission intensity of a sample without bubbles. For some applications, the height of the chamber varies in different ways, but generally similar techniques are performed with corresponding modifications.

[0294] Thus, according to some applications of the present invention, in addition to measuring the absolute value of a parameter indicating light transmission along the length of the sample chamber, a normalized value of a parameter indicating light transmission along the sample chamber (e.g., the normalized logarithm of the light transmission intensity) is determined. Based on the normalized value of the parameter, a computer processor determines that there may be bubbles (e.g., the presence of air bubbles or different substances) within the sample chamber. For some applications, in response to determining that there may be bubbles within the sample chamber, the computer processor generates an output. For example, the computer processor may generate an error message (e.g., a message indicating that the sample chamber should be refilled), may invalidate the sample, and / or may invalidate a part of the measurement performed on the sample.

[0295] For some applications, the computer processor performs light absorption measurements, but only uses regions within the chamber where there are no bubbles for the measurement. Thus, for some applications, based on the absolute value of a parameter indicating light transmission at at least some regions within the sample chamber, the computer processor calculates the hemoglobin concentration within the sample. Additionally, the computer processor normalizes the parameters measured at various regions within the sample chamber relative to each other. At least in part in response to the normalized parameters, the computer processor determines which region to use for calculating the hemoglobin concentration within the sample. Alternatively, the computer processor may invalidate the sample and not use it for calculating the hemoglobin concentration within the sample, and / or may generate an error message (e.g., a message indicating that the sample chamber should be refilled).

[0296] Along the width of the chamber, it is desirable for the sample to have a relatively constant absorption profile. For some applications, the computer processor is configured to interpret an unexpectedly low absorption level (not conforming to the above profile) as indicating the presence of air bubbles. For some applications, to determine the presence of air bubbles, one or more light absorption measurements are performed at wavelengths at which hemoglobin does not absorb light (e.g., using green light). Alternatively or additionally, a camera (e.g., a CCD camera or a CMOS camera of a microscope) is used to image a second portion of the blood sample, and the computer processor determines the presence of air bubbles based on the image.

[0297] Generally, based on the optical measurements, one or more parameters of the sample are determined by the computer processor. For some applications, based on determining that one or more air bubbles are present in the chamber, at least some of the optical measurements are rendered invalid for use in determining one or more parameters of the sample. For some applications, the computer processor generates an output based on determining that one or more air bubbles are present in the sample chamber, the output indicating that a portion of the blood sample has been rendered invalid for performing at least some measurements on the sample.

[0298] For some applications, a similar technique is generally performed on a first portion of the blood sample placed in the sample chambers of the first set 52. For example, the computer processor may be configured to identify regions within the microscopic image of the sample chamber where the sample is absent and render at least the identified regions invalid for use in the microscopic analysis of a portion of the sample. For some applications, the computer processor is configured to identify such regions by identifying the interface between the wet and dry regions on the base surface of the sample chamber. Generally, in identifying such regions, the computer processor is configured to distinguish regions where the sample is absent from regions where the sample is present and the sample has a low cell density.

[0299] For some applications, the computer processor is configured to identify the presence of dirt (e.g., spilled blood) on the outer surface of the sample carrier. As described above, generally, at least one microscopic image of the cell monolayer that has settled on the base surface of the sample carrier is acquired. Generally, the image is acquired when the microscope is focused on the monolayer focal plane, where the cell monolayer is disposed within the monolayer focal plane. For some applications, the computer processor identifies regions where the dirt is disposed on the top cover of the sample carrier or on the underside of the base surface by identifying regions where an entity is visible at a focal plane different from the monolayer focal plane. Alternatively or additionally, the computer processor identifies regions where the background intensity of the microscopic image (acquired at the monolayer focal plane) indicates that the dirt is disposed on the top cover or on the underside of the base surface. For some applications, in response thereto, the computer processor renders at least the identified regions invalid for use in the microscopic analysis of that portion of the sample.

[0300] As described above, typically, a first portion of a blood sample is imaged under brightfield imaging, i.e., under illumination from one or more brightfield light sources (e.g., one or more brightfield light-emitting diodes, which typically emit light in respective spectral bands). Additionally, typically, the first portion of the blood sample is further imaged under fluorescence imaging. Typically, fluorescence imaging is performed by directing light at the sample at a known excitation wavelength (i.e., wavelengths at which, if excited by light at those wavelengths, the stained objects within the sample are known to emit fluorescence) to excite the stained objects within the sample and detecting the fluorescence. Typically, for fluorescence imaging, a separate set of one or more fluorescence light-emitting diodes is used to illuminate the sample at the known excitation wavelength.

[0301] For some applications, a computer processor analyzes the light emitted by the brightfield light source and determines the characteristics of the brightfield light source. For example, the computer processor can periodically determine whether the spatial distribution of the illumination of the brightfield light source has changed since the previous measurement (e.g., whether the spatial uniformity of the illumination has changed or the spatial position has changed since the previous measurement), whether the vignetting effect of the illumination of the brightfield light source has changed since the previous measurement, whether the spectral distribution of the illumination of the brightfield light source has changed since the previous measurement, and / or whether the intensity of the illumination of the brightfield light source has changed since the previous measurement. As described above, typically, the computer processor determines the parameters of the blood sample by performing measurements on entities identified within a microscopic image of the blood sample. For some applications, these measurements are normalized based on the determined characteristics of the brightfield light source. For some applications, based on the determined characteristics of the brightfield light source, at least some measurements are invalidated without performing them on the blood sample.

[0302] For some applications, to determine the characteristics of the brightfield light source, the computer processor analyzes the light emitted by the brightfield light source in the absence of the sample carrier. Alternatively or additionally, the computer processor analyzes the light emitted by the brightfield light source that passes through the intercellular regions within the blood sample.

[0303] For some applications, a computer processor analyzes light emitted by a fluorescent light source and determines characteristics of the fluorescent light source. For example, the computer processor may periodically determine whether the spatial distribution of the illumination by the fluorescent light source has changed since the previous measurement (e.g., whether the spatial uniformity of the illumination has changed since the previous measurement or whether the spatial position has changed since the previous measurement), whether the vignetting effect of the illumination by the fluorescent light source has changed since the previous measurement, whether the spectral distribution of the illumination by the fluorescent light source has changed since the previous measurement, and / or whether the intensity of the illumination by the fluorescent light source has changed since the previous measurement. As described above, generally, the computer processor determines parameters of a blood sample by performing measurements on entities identified within a microscopic image of the blood sample. For some applications, these measurements are normalized based on the determined characteristics of the fluorescent light source. For some applications, based on the determined characteristics of the fluorescent light source, at least some of the measurements are invalidated without performing them on the blood sample.

[0304] For some applications, to determine the characteristics of the fluorescent light source, the computer processor identifies one or more fluorescent regions visible within a microscopic image obtained under illumination by the fluorescent light source and that are other than stained cells, and determines the characteristics of the fluorescent light source based on the identified fluorescent regions. For example, such fluorescent regions may include intercellular regions within the blood sample, one or more fluorescent regions of the microscopic unit, and / or one or more fluorescent regions of the sample carrier (e.g., the pressure-sensitive adhesive of the sample carrier described above). For some applications, the sample carrier is placed on a stage within the microscopic unit, and the stage includes a fluorescent region for performing the above-described measurements. Alternatively or additionally, the sample carrier includes a fluorescent region (e.g., a fluorescent patch) for performing the above-described measurements.

[0305] For some applications, the computer processor is configured to detect whether there is dirt or a scratch on a part of the microscopic unit (such as a CCD camera, a CMOS camera, a lens, and / or the stage for holding the sample carrier) by acquiring a microscopic image without any sample carrier and identifying dirt or a scratch in such an image. For some applications, such an image is acquired periodically (e.g., at fixed time intervals) to determine whether the microscopic unit has dirt or a scratch on this part of the microscopic unit. For some applications, in response to detecting such dirt and / or a scratch, this will be marked for the user. Alternatively or additionally, the regions within the image corresponding to the locations where the dirt and / or the scratch are present are not included in at least some of the image analysis of the sample. Further alternatively or additionally, the measurements performed on the regions within the image corresponding to the locations where the dirt and / or the scratch are present are calibrated to account for the dirt and / or the scratch.

[0306] For some applications, a computer processor is configured to detect whether a portion of a sample carrier has dirt or scratches using techniques generally similar to the foregoing techniques. For example, the sample carrier can be imaged when there is no sample therein. For some applications, the computer processor is configured to detect whether a portion of the sample carrier fluoresces irregularly, for example, by imaging the sample carrier when there is no sample therein.

[0307] For some applications, in response to detecting an error in at least some fluorescence microscopy images, the computer processor classifies the source of the error as follows. In response to detecting that the error was introduced at a given point in time, the computer processor identifies the dye as the source of the error, as this indicates that the error was introduced due to using a new batch of dye. In response to detecting that the error increases gradually over time, the computer processor identifies dirt within the microscopy unit as the source of the error, as such dirt typically causes a gradual degradation over time. In response to detecting that the error is present only in images acquired under a given one of the light sources (e.g., a light-emitting diode), the computer processor identifies the given one of the light sources as the source of the error.

[0308] For some applications, the optical measurement unit includes a microscope that includes a microscope stage on which the sample carrier is typically placed. Generally, the computer processor drives the movement of the microscope stage using one or more motors for driving the movement of mechanical elements. In some cases, there is a certain degree of recoil associated with the movement of the mechanical elements. For example, when the direction of movement is initiated or reversed, there may be a delay between the computer-implemented instructions sent to the motor and the movement of the mechanical elements that is implemented. For some applications, the computer processor takes this effect into account when performing any movement (e.g., by assuming a given fixed delay exists, or by periodically measuring the delay and considering the most recently measured delay). For some applications, a microscopy system is used to quantify the amount of recoil, and the amount of recoil is interpreted as indicating the condition of the mechanical elements and / or the motor. For example, the amount of recoil can be quantified by observing how many motor steps are required to produce a recognizable movement in the microscopy system, and / or by repeating the same measurement in two different directions of movement, and correlating between the images or between metrics extracted from the images associated with the movement in the two different directions. For some applications, based on the foregoing measurements, the state of the mechanical elements and / or the motor is determined. For some applications, an output is generated in response to the determined state of the mechanical elements and / or the motor. For example, at least some images (and / or data related to the sample) of the sample can be rejected, the microscope and / or other parts of the optical measurement unit can be locked so that they cannot be used, and / or an alert can be generated (e.g., an alert indicating that repair is needed and / or an alert indicating a reasonable preemptive repair can be generated).

[0309] For some applications, microscopic images (and / or other signals) are acquired during stage movement. For some such applications, there may be a timing mismatch between the reported or interpolated position of the stage at a given time and the actual timing of acquisition by a camera or sensor at that position. This can lead to errors in the assumed position at which a given image (or data) is acquired, and subsequently, if that position is used for other purposes (e.g., if the image (or the data) and the corresponding position are used as input for focusing the microscope), it can lead to additional errors. For some applications, such timing mismatches are measured, for example, by using two measurements of the same target as follows. A first image of the target (or a data set associated with the target) is acquired using static acquisition along a mechanical axis, and a second image of the target (or a data set associated with the target) is acquired using acquisition during stage movement. The differences between the images or the differences between the metrics extracted from the images (and / or the differences between the two data sets) are detected, and if such differences are detected, the computer processor uses them as input for determining the presence of a timing mismatch and / or for correcting the timing mismatch. For some applications, such measurements are made periodically and are used as input for determining the state of parts of an optical measurement system (e.g., parts of a microscope system, including the image acquisition part, mechanical elements, and / or motors). For some applications, an output is generated in response to detecting the presence of a timing mismatch and / or a difference relative to a previous measurement. For example, at least some images (and / or data related to the sample) of the analyzed sample can be rejected, other parts of the microscope and / or the optical measurement unit can be locked so that they cannot be used, and / or an alert can be generated (e.g., an alert indicating that maintenance is required and / or an alert indicating reasonable preemptive maintenance).

[0310] For some applications, the state of an optical measurement unit (e.g., a microscope of an optical measurement system, and / or a light absorption measurement portion of the optical measurement unit) is estimated by imaging an object mounted within the optical measurement unit itself (or conventionally input into the optical measurement unit). For example, a scratched glass surface, a printed glass surface, one or more fluorescent or non-fluorescent beads, a pinhole, or any other resolution target may be used. For some applications, by acquiring and analyzing an image of such an object (and / or data associated therewith), a computer processor derives optical properties of the optical measurement unit, such as aberration, resolution, contrast, scattering, and attenuation. For some applications, the computer processor periodically performs such an analysis and compares the determined properties to predetermined values. For some applications, in response to detecting a difference between one or more of the determined properties and the predetermined values, an output is generated. For example, at least some images of an analyzed sample (and / or data related to the sample) may be rejected, the microscope and / or other portions of the optical measurement unit may be locked so that they cannot be used, and / or an alert may be generated (e.g., an alert indicating that repair is needed and / or an alert indicating reasonable preemptive repair). For some applications, based on the determined properties, the computer processor corrects the extracted image features, (in the case of non-imaging measurements) the measured values, and / or the analyte of the sample. For example, absorption measurements may be corrected due to a change in apparent contrast in the object.

[0311] For some applications, the sample described herein is a sample comprising blood or a component thereof (e.g., a diluted or undiluted whole blood sample, a sample predominantly comprising red blood cells, or a diluted sample predominantly comprising red blood cells), and parameters related to components in blood such as platelets, white blood cells, abnormal white blood cells, circulating tumor cells, red blood cells, reticulocytes, Howell-Jolly bodies, etc. are determined.

[0312] Generally, it should be noted that although some applications of the present invention have been described with respect to blood samples, the scope of the present invention includes applying the devices and methods described herein to various samples. For some applications, the sample is a biological sample such as blood, saliva, semen, sweat, sputum, vaginal secretions, feces, breast milk, bronchoalveolar lavage, gastric lavage, tears, and / or nasal mucus. The biological sample may be from any living organism and is typically from a warm-blooded animal. For some applications, the biological sample is a sample from a mammal, e.g., a sample from a human body. For some applications, the sample is taken from any domestic animal, zoo animal, and farm animal, including but not limited to dogs, cats, horses, cows, and sheep. Alternatively or additionally, the biological sample is taken from an animal that is a disease vector, including deer or mice.

[0313] For some applications, techniques similar to those described above are applied to non-body samples. For some applications, the sample is an environmental sample, such as a water (e.g., groundwater) sample, a surface swab, a soil sample, an air sample, or any combination thereof. In some embodiments, the sample is a food sample, such as a meat sample, a dairy sample, a water sample, a wash sample, a beverage sample, and / or any combination thereof.

[0314] The applications of the invention described herein may take the form of a computer program product accessible from a computer-usable or computer-readable medium (e.g., a non-transitory computer-readable medium) that provides program code for use by a computer or any instruction execution system, such as computer processor 28, or that is related to a computer or any instruction execution system (e.g., computer processor 28). For the purposes of this description, a computer-usable or computer-readable medium can be any device that can comprise, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The medium can be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device) or a propagation medium. Generally, a computer-usable or computer-readable medium is a non-transitory computer-usable or computer-readable medium.

[0315] Examples of computer-readable media include semiconductor or solid state memory, magnetic tape, removable computer diskettes, random access memory (RAM), read only memory (ROM), hard disk, and optical disk. Current examples of optical disks include compact disk-read only memory (CR-ROM), compact disk-read / write (CD-R / W), and DVD.

[0316] A data processing system suitable for storing and / or executing program code will include at least one processor (e.g., computer processor 28) coupled directly or indirectly to memory elements (e.g., memory 30) through a system bus. The memory elements can include local memory employed during actual execution of the program code, bulk storage, and cache memory that provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during execution. The system can read the instructions of the invention on a program storage device and follow those instructions to execute the methods of embodiments of the invention.

[0317] A network adapter can be coupled to the processor to enable the processor to be coupled to other processors or remote printers or storage devices through an intervening private or public network. Modems, cable modems, and Ethernet cards are just a few of the currently available types of network adapters.

[0318] The computer program code for performing the operations of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, Smalltalk, C++, etc., and conventional procedural programming languages such as the "C" programming language or similar programming languages.

[0319] It will be understood that the algorithms described herein can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus for manufacturing a machine, such that the instructions executed via the processor of a computer (e.g., computer processor 28) or other programmable data processing apparatus produce a means for implementing the functions / acts specified in the algorithms described in the present application. These computer program instructions can also be stored in a computer-readable medium (e.g., a non-transitory computer-readable medium), which can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture that includes instruction means for implementing the functions / acts specified in the process blocks and algorithms. The computer program instructions can also be loaded into a computer or other programmable data processing apparatus, so as to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions executed on the computer or other programmable apparatus provide a process for implementing the functions / acts specified in the algorithms described in the present application.

[0320] The computer processor 28 is generally a hardware device programmed with computer program instructions to produce a special-purpose computer. For example, when programmed to execute the algorithms described herein, the computer processor 28 generally acts as a special-purpose sample analysis computer processor. Generally, the operations performed by the computer processor 28 described herein convert the physical state of the memory 30 into different magnetic polarities, charges, etc. according to the technology of the memory used, and the memory 30 is a real physical article.

[0321] The devices and methods described herein can be used in combination with the devices and methods described in any of the following patent applications, all of which are incorporated herein by reference:

[0322] US 2012 / 0169863 of Bachelet;

[0323] US 2014 / 0347459 of Greenfield;

[0324] US 2015 / 0037806 of Pollak;

[0325] US 2015 / 0316477 of Pollak;

[0326] Pollak's US 2016 / 0208306;

[0327] Yorav Raphael's US 2016 / 0246046;

[0328] Bachelet's US 2016 / 0279633;

[0329] Eshel's US 2018 / 0246313;

[0330] Yorav Raphael's WO 16 / 030897;

[0331] Eshel's WO 17 / 046799;

[0332] Eshel's WO 17 / 168411;

[0333] Pollack's WO 17 / 195205;

[0334] Zait's US 2019 / 0145963; and

[0335] Yorav Raphael's WO 19 / 097387.

[0336] Those skilled in the art will recognize that the present invention is not limited to what has been specifically shown and described above. Rather, the scope of the present invention includes combinations and sub - combinations of the various features described above, as well as variations and modifications thereof that will occur to those skilled in the art after reading the above description and that are not in the prior art.

Claims

1. A method for measuring a blood sample, comprising: placing at least a portion of the blood sample in a sample chamber; acquiring a microscopic image of a portion of the blood sample; identifying candidates for a given entity within the blood sample in the microscopic image; verifying at least some of the candidates as the given entity by performing further analysis on the candidates; comparing the count of candidates for the given entity with the count of verified candidates for the given entity; and at least partially based on the relationship between the count of candidates and the count of verified candidates, rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample, wherein rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample includes: rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample based on the ratio of the count of verified candidates to the count of candidates exceeding a maximum threshold; and / or wherein rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample includes: rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample based on the ratio of the count of verified candidates to the count of candidates being less than a minimum threshold.

2. The method according to claim 1, wherein: identifying candidates for a given entity within the blood sample in the microscopic image includes identifying platelet candidates within the blood sample in the microscopic image; verifying at least some of the candidates as the given entity by performing further analysis on the candidates includes: verifying at least some of the platelet candidates as platelets by performing further analysis on the candidates; and rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample includes: at least partially based on the relationship between the count of platelet candidates and the count of verified platelet candidates, rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample.

3. The method according to claim 1, wherein: identifying candidates for a given entity within the blood sample in the microscopic image includes identifying white blood cell candidates within the blood sample in the microscopic image; verifying at least some of the candidates as the given entity by performing further analysis on the candidates includes: verifying at least some of the white blood cell candidates as white blood cells by performing further analysis on the candidates; and rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample includes: at least partially based on the relationship between the count of white blood cell candidates and the count of verified white blood cell candidates, rendering at least a portion of the sample invalid for use in performing at least some measurements on the sample.

4. A method for measuring a blood sample, comprising: placing at least a portion of the blood sample in a sample chamber; acquiring a microscopic image of a portion of the blood sample; Identify leukocyte candidates in the blood sample within the microscopic image; Verify at least some of the leukocyte candidates as leukocytes of a given type by performing further analysis on the leukocyte candidates; Compare the count of the leukocyte candidates with the count of the leukocyte candidates that are verified as leukocytes of the given type; and At least partially based on the relationship between the count of the leukocyte candidates and the count of the leukocyte candidates that are verified as leukocytes of a given type, invalidate at least a portion of the sample from being used to perform at least some measurements on the sample, wherein invalidating at least a portion of the sample from being used to perform at least some measurements on the sample includes: invalidating at least a portion of the sample from being used to perform at least some measurements on the sample based on the ratio of the count of the verified candidates to the count of the candidates exceeding a maximum threshold; and / or wherein invalidating at least a portion of the sample from being used to perform at least some measurements on the sample includes: invalidating at least a portion of the sample from being used to perform at least some measurements on the sample based on the ratio of the count of the verified candidates to the count of the candidates being less than a minimum threshold.

5. A blood sample measurement device, comprising: A sample chamber configured to receive a blood sample; A microscope configured to acquire at least one microscopic image of the blood sample; and A computer processor configured to: Identify candidates for a given entity in the blood sample within the microscopic image; Verify at least some of the candidates as the given entity by performing further analysis on the candidates; Compare the count of the candidates for the given entity with the count of the verified candidates for the given entity; and At least partially based on the relationship between the count of the candidates and the count of the verified candidates, invalidate at least a portion of the sample from being used to perform at least some measurements on the sample, wherein the computer processor is configured to invalidate at least a portion of the sample from being used to perform at least some measurements on the sample by invalidating at least a portion of the sample from being used to perform at least some measurements on the sample based on the ratio of the count of the verified candidates to the count of the candidates exceeding a maximum threshold; and / or wherein the computer processor is configured to invalidate at least a portion of the sample from being used to perform at least some measurements on the sample by invalidating at least a portion of the sample from being used to perform at least some measurements on the sample based on the ratio of the count of the verified candidates to the count of the candidates being less than a minimum threshold.

6. The device according to claim 5, wherein the computer processor is configured to: Identify candidates for platelets in the blood sample within the microscopic image, thereby identifying candidates for a given entity in the blood sample within the microscopic image; Verifying at least some of the platelet candidates as platelets by performing further analysis on the candidates, thereby verifying at least some of the candidates as the given entity by performing further analysis on the candidates; and Invalidating at least a portion of the sample from being used to perform at least some measurements on the sample by at least partially based on the relationship between the count of platelet candidates and the count of verified platelet candidates, thereby invalidating at least a portion of the sample from being used to perform at least some measurements on the sample.

7. The apparatus according to claim 5, wherein, the computer processor is configured to: Identify leukocyte candidates in the blood sample within the microscopic image, thereby identifying candidates for a given entity within the blood sample within the microscopic image; Verify at least some of the leukocyte candidates as leukocytes by performing further analysis on the candidates, thereby verifying at least some of the candidates as the given entity by performing further analysis on the candidates; and Invalidate at least a portion of the sample from being used to perform at least some measurements on the sample by at least partially based on the relationship between the count of leukocyte candidates and the count of verified leukocyte candidates, thereby invalidating at least a portion of the sample from being used to perform at least some measurements on the sample.

8. A blood sample measurement apparatus, comprising: A sample chamber configured to receive a blood sample; A microscope configured to acquire at least one microscopic image of the blood sample; and A computer processor configured to: Identify leukocyte candidates in the blood sample within the microscopic image; Verify at least some of the leukocyte candidates as leukocytes of a given type by performing further analysis on the leukocyte candidates; Compare the count of the leukocyte candidates with the count of the leukocyte candidates verified as leukocytes of the given type; and Invalidate at least a portion of the sample from being used to perform at least some measurements on the sample at least partially based on the relationship between the count of the leukocyte candidates and the count of the leukocyte candidates verified as leukocytes of a given type, wherein the computer processor is configured to invalidate at least a portion of the sample from being used to perform at least some measurements on the sample by based on the ratio of the count of verified candidates to the count of candidates exceeding a maximum threshold, thereby invalidating at least a portion of the sample from being used to perform at least some measurements on the sample; and / or wherein the computer processor is configured to invalidate at least a portion of the sample from being used to perform at least some measurements on the sample by based on the ratio of the count of verified candidates to the count of candidates being less than a minimum threshold, thereby invalidating at least a portion of the sample from being used to perform at least some measurements on the sample.

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