Off-focus microscope image of the sample

Abstract

The present invention provides an apparatus and method for use with bodily samples containing cells. The method includes focusing a microscope (24) so ​​that its focal plane at least approximately coincides with a level at which at least some cells that are part of the sample are at least partially located. At least one on-focus microscope image of the sample is acquired with the focal plane of the microscope (24) approximately coincident with the level. The method includes focusing the microscope (24) so ​​that its focal plane is offset from the level. At least one off-focus microscope image of the sample is acquired with the focal plane of the microscope (24) offset from the level. A characteristic of at least a portion of the sample is determined based at least in part on the on-focus and off-focus images. Other applications are also described.

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims priority to U.S. Provisional Patent Application No. US 62 / 946,985 to Gluck et al., filed December 12, 2019, and U.S. Provisional Patent Application No. US 63 / 048,692 to Gluck et al., filed July 7, 2020, both entitled "Distinguishing between NRBCs and leukocytes," both of which are incorporated herein by reference.

[0002] Some applications of the subject matter disclosed herein relate generally to the analysis of body samples, and specifically to optical density and microscopic measurements performed on blood samples. [Background technology]

[0003] In some optically-based methods (e.g., diagnostic and / or analytical methods), properties of a biological sample, such as a blood sample, are determined by performing optical measurements. For example, component density (e.g., number of components per unit volume) can be determined by counting components in a microscopic image. Similarly, component concentration and / or density can be measured by performing optical absorption, transmittance, fluorescence, and / or luminescence measurements on the sample. Typically, the sample is placed on a sample carrier, and measurements are performed on a portion of the sample contained within the sample chamber of the sample carrier. The measurements performed on the portion of the sample contained within the sample chamber of the sample carrier are analyzed to determine properties of the sample.

[0004] Mammalian red blood cells (i.e., erythrocytes) are the body's oxygen carriers. During the maturation process, red blood cells undergo denucleation, i.e., the complete removal of the nucleus from the cell. Normally, nucleated red blood cells (NRBCs) are not detectable in the peripheral blood of adult patients. However, in some conditions (e.g., newborns, cancer patients, and patients with anemia), NRBCs can be detected in the peripheral blood. Summary of the Invention

[0005] As mentioned in the Background section, mammalian red blood cells are the body's oxygen carriers. During the maturation process, red blood cells are enucleated, i.e., the nucleus is completely removed from the cell. Normally, nucleated red blood cells (NRBCs) are not detectable in the peripheral blood of adult patients. However, in some conditions (e.g., newborns, cancer patients, and patients with anemia), NRBCs are detectable in peripheral blood. Because NRBCs are similar in size and nuclear content to some white blood cells (especially lymphocytes), it is usually difficult to distinguish NRBCs from white blood cells. In some applications of the present invention, a complete blood count is performed on a blood sample. In the context of a complete blood count, it is typically important to distinguish between NRBCs and white blood cells to avoid overcounting white blood cells (especially in patients with low white blood cell counts) and to detect the presence of NRBCs, which may indicate an underlying disease.

[0006] According to some applications of the present invention, to distinguish between white blood cells (e.g., lymphocytes) and NRBCs (e.g., in situations where NRBC / white blood cell candidates (i.e., candidates that may be either NRBCs or white blood cells) are detected), a microscope image is acquired while illuminating the sample with light of a wavelength at which hemoglobin has a high level of absorption. Typically, violet light is used, e.g., light having a wavelength greater than 400 nm and / or less than 450 nm (e.g., 400-450 nm). (It should be noted that there is some variation in the literature regarding the wavelength range referred to as being within the violet range. For purposes of this application, violet light should be interpreted as including light within the 400-450 nm range.) Within this wavelength range, hemoglobin has a relatively high absorption compared to other wavelengths in the visible spectrum. NRBCs typically have a high hemoglobin content (on the order of 30 picograms per cell), while white blood cells contain no hemoglobin. Thus, in images acquired under violet light illumination, NRBCs typically absorb light, whereas white blood cells do not.

[0007] Typically, NRBC / leukocyte candidates are classified as either NRBCs or leukocytes based at least in part on the intensity of the NRBC / leukocyte candidates in images acquired under violet illumination. In some applications, an intensity threshold is applied to the image acquired under violet illumination conditions (and / or to a given region or pixel thereof), and the NRBC / leukocyte candidates are classified as either NRBCs or leukocytes based on whether the intensity of the NRBC / leukocyte candidates exceeds this threshold.

[0008] Some applications involve performing techniques generally similar to those described above, but using light having wavelengths greater than 500 nm and / or less than 600 nm (e.g., 500-600 nm), within which carbaminohemoglobin has relatively high absorption compared to other wavelengths in the visible spectrum.

[0009] According to some applications of the present invention, a portion of a blood sample containing a cell suspension is placed in a sample chamber of a carrier. The sample chamber is a cavity including a base surface. Typically, cells in the cell suspension are allowed to settle onto the base surface of the sample chamber to form a monolayer of cells on the base surface of the sample chamber. After allowing the cells to settle on the base surface of the sample chamber (e.g., by allowing them to settle for a predetermined time period), at least one microscopic image of at least a portion of the monolayer of cells is typically acquired.

[0010] In some applications, a microscope acquires images by setting the microscope focal plane to approximately coincide with the monolayer focus level (such images are referred to herein as “on-focus images”), and also acquires images by setting the microscope focal plane to be offset along the optical axis relative to the monolayer focus level (such images are referred to herein as “off-focus images”). Typically, such off-focus microscope images are acquired by setting the microscope focal plane closer to the microscope objective lens than the monolayer focus level, but the scope of the present invention includes acquiring off-focus images by setting the microscope focal plane farther from the microscope objective lens than the monolayer focus level. In some applications, off-focus microscope images are acquired by setting the microscope focal plane to be offset from the monolayer focus level by more than 20 microns and / or less than 100 microns, e.g., 20-100 microns. Alternatively or additionally, the off-focus microscope image is acquired by setting the microscope focal plane to a monolayer focus level at more than 1x the microscope focal depth and / or less than 5x the microscope focal depth, for example, an offset of 1 to 5 microscope focal depths.

[0011] The inventors of the present application have discovered that such off-focus microscopic images can yield important data about a sample. Specifically, off-focus images are typically used to identify cellular contours and / or identify specific entities within a sample. These entities include, for example, white blood cells, white blood cell types (e.g., lymphocytes, granulocytes, monocytes, neutrophils, banded neutrophils, eosinophils, basophils, macrophages, and / or blast cells), red blood cells, red blood cell types (e.g., mature red blood cells, NRBCs, echinocytes, sickle cells, teardrop cells), and / or platelets. In some applications, off-focus images are used to improve the visibility of such entities relative to other entities, allowing them to be identified with greater certainty. Alternatively or additionally, off-focus images are used to facilitate distinguishing such entities from other entities with which they might otherwise be confused. In some applications, off-focus images are used to show cellular characteristics such as the hemoglobin content of red blood cells, other components of red blood cells, and / or the maturity of the cells (e.g., neutrophils).

[0012] Thus, according to some applications of the present invention, there is provided a method for use with a bodily sample containing cells, the method comprising: focusing the microscope so that the focal plane of the microscope is at least approximately coincident with a level at which at least some cells that are part of the sample are at least partially disposed; acquiring at least one on-focus microscope image of the sample with the focal plane of the microscope approximately level; focusing the microscope so that the focal plane of the microscope is offset relative to the level; acquiring at least one off-focus microscope image of the sample with the focal plane of the microscope offset relative to the level; determining a property of at least a portion of the sample based at least in part on the on-focus and off-focus images; Includes.

[0013] In some applications, acquiring at least one off-focus microscope image of the sample with the focal plane of the microscope offset relative to the level includes acquiring at least one off-focus microscope image of the sample with the focal plane of the microscope offset relative to the level by a predetermined offset.

[0014] In some applications, determining at least a portion of the characteristics of the sample based at least in part on the on-focus and off-focus images includes inputting the on-focus and off-focus images to a machine learning classifier, the machine learning classifier configured to determine at least a portion of the characteristics of the sample based at least in part on the on-focus and off-focus images.

[0015] In some applications, determining a characteristic of at least a portion of the sample based at least in part on the on-focus and off-focus images includes deriving one or more parameters from the on-focus and off-focus images and inputting the one or more derived parameters to a machine learning classifier, wherein the machine learning classifier is configured to determine a characteristic of at least a portion of the sample based at least in part on the derived parameters.

[0016] In some applications, the sample includes a blood sample, and acquiring at least one off-focus microscopic image of the sample with the focal plane of the microscope offset relative to the level includes acquiring at least one off-focus microscopic image of the sample while illuminating the sample with light having a wavelength between 505 nm and 535 nm.

[0017] In some applications, the sample includes a blood sample, and acquiring at least one off-focus microscopic image of the sample with the focal plane of the microscope offset relative to the level includes acquiring at least one off-focus microscopic image of the sample while illuminating the sample with light having a wavelength between 400 nm and 450 nm.

[0018] In some applications, the sample includes a blood sample, and acquiring at least one off-focus microscopic image of the sample with the focal plane of the microscope offset relative to the level includes acquiring at least one off-focus microscopic image of the sample while illuminating the sample with light having a wavelength between 620 nm and 640 nm.

[0019] In some applications, focusing the microscope so that the focal plane of the microscope is offset relative to the level includes focusing the microscope so that the focal plane of the microscope is set closer to the microscope objective than the level at which at least some cells that are part of the sample are at least partially located.

[0020] In some applications, focusing the microscope so that the focal plane of the microscope is offset relative to a level includes focusing the microscope so that the focal plane of the microscope is set farther from the microscope objective than a level at which at least some cells that are part of the sample are at least partially located.

[0021] In some applications, focusing the microscope so that the focal plane of the microscope is offset relative to the level includes focusing the microscope so that the focal plane of the microscope is offset by 20 microns to 100 microns relative to the level on which at least some cells that are part of the sample are at least partially located.

[0022] In some applications, focusing the microscope so that the focal plane of the microscope is offset relative to the level includes focusing the microscope so that the focal plane of the microscope is offset by 1 to 5 focal depths of the microscope relative to a level on which at least some cells that are part of the sample are at least partially located.

[0023] In some applications, the method further includes settling some cells in the sample to form a monolayer at a monolayer focal level, and focusing the microscope so that the focal plane of the microscope at least approximately coincides with a level at which at least some cells that are part of the sample are at least partially located includes focusing the microscope so that the focal plane of the microscope at least approximately coincides with the monolayer focal level.

[0024] In some applications, the method further includes allowing some cells in the sample to settle to form a monolayer at the monolayer focal level, and other cells in the sample being suspended at at least one additional level within the sample, and focusing the microscope so that the focal plane of the microscope at least approximately coincides with the level at which at least some cells that are part of the sample are at least partially located includes focusing the microscope so that the focal plane of the microscope at least approximately coincides with the additional level at which other cells in the sample are suspended.

[0025] In some applications, determining a property of the portion of the sample based at least in part on the on-focus and off-focus images includes normalizing the on-focus and off-focus images relative to one another and determining a property of the portion of the sample based at least in part on the normalization.

[0026] In some applications, the sample includes a blood sample, and determining a characteristic of a portion of the sample based at least in part on the on-focus and off-focus images includes identifying one or more entities within the blood sample based at least in part on the on-focus and off-focus images, wherein the one or more entities are selected from the group consisting of platelets, leukocytes, lymphocytes, granulocytes, monocytes, neutrophils, striped neutrophils, eosinophils, basophils, and macrophages.

[0027] In some applications, the sample includes a blood sample, and determining a characteristic of a portion of the sample based at least in part on the on-focus and off-focus images includes identifying blast cells within the blood sample based at least in part on the on-focus and off-focus images.

[0028] In some applications, determining a characteristic of a portion of the sample based at least in part on the on-focus and off-focus images includes identifying contours of one or more entities within the sample based at least in part on the on-focus and off-focus images.

[0029] In some applications, determining a characteristic of a portion of the sample based at least in part on the on-focus and off-focus images further includes estimating parameters of one or more entities based at least in part on the identified contour, the parameters being selected from the group consisting of cell area and cell volume.

[0030] In some applications, determining a characteristic of a portion of the sample based at least in part on the on-focus and off-focus images further includes estimating a parameter of the sample based at least in part on the identified contour, wherein the at least one parameter is selected from the group consisting of an average cell area and an average cell volume.

[0031] Further, in accordance with some applications of the present invention, there is provided an apparatus for use with a bodily sample containing cells, the apparatus comprising: A microscope and 1. A computer processor comprising: focusing the microscope so that the focal plane of the microscope is at least approximately coincident with a level at which at least some cells that are part of the sample are at least partially disposed; With the microscope focal plane approximately level, drive the microscope to acquire at least one on-focus microscope image of the sample. Focus the microscope so that the focal plane of the microscope is offset relative to the level. Drive the microscope to acquire at least one off-focus microscope image of the sample with the focal plane of the microscope offset relative to the level; determining a property of at least a portion of the sample based at least in part on the on-focus and off-focus images; a computer processor configured to: Equipped with.

[0032] Further, in accordance with some applications of the present invention, there is provided a method for use with a bodily sample containing cells, the method comprising: focusing the microscope so that the focal plane of the microscope is offset relative to a level at which at least some cells that are part of the sample are at least partially located; acquiring at least one off-focus microscope image of the sample with the focal plane of the microscope offset relative to the level; performing one or more operations selected from the group consisting of identifying entities located within the level based at least in part on the off-focus image, determining contours of entities located within the level, determining parameters of entities located within the level, determining parameters of samples, and any combination thereof; Includes.

[0033] In some applications, acquiring at least one off-focus microscope image of the sample with the focal plane of the microscope offset relative to the level includes acquiring at least one off-focus microscope image of the sample with the focal plane of the microscope offset relative to the level by a predetermined offset.

[0034] In some applications, performing one or more actions based at least in part on the off-focus image includes inputting the off-focus image to a machine learning classifier, the machine learning classifier configured to perform one or more actions based at least in part on the off-focus image.

[0035] In some applications, performing one or more actions based at least in part on the off-focus image includes deriving one or more parameters from the off-focus image and inputting the one or more derived parameters to a machine learning classifier, the machine learning classifier configured to perform the one or more actions based at least in part on the derived parameters.

[0036] In some applications, the sample includes a blood sample, and acquiring at least one off-focus microscopic image of the sample with the focal plane of the microscope offset relative to the level includes acquiring at least one off-focus microscopic image of the sample while illuminating the sample with light having a wavelength between 505 nm and 535 nm.

[0037] In some applications, the sample includes a blood sample, and acquiring at least one off-focus microscopic image of the sample with the focal plane of the microscope offset relative to the level includes acquiring at least one off-focus microscopic image of the sample while illuminating the sample with light having a wavelength between 400 nm and 450 nm.

[0038] In some applications, the sample includes a blood sample, and acquiring at least one off-focus microscopic image of the sample with the focal plane of the microscope offset relative to the level includes acquiring at least one off-focus microscopic image of the sample while illuminating the sample with light having a wavelength between 620 nm and 640 nm.

[0039] In some applications, focusing the microscope so that the focal plane of the microscope is offset relative to the level includes focusing the microscope so that the focal plane of the microscope is set closer to the microscope objective than the level at which at least some cells that are part of the sample are at least partially located.

[0040] In some applications, focusing the microscope so that the focal plane of the microscope is offset relative to a level includes focusing the microscope so that the focal plane of the microscope is set farther from the microscope objective than a level at which at least some cells that are part of the sample are at least partially located.

[0041] In some applications, focusing the microscope so that the focal plane of the microscope is offset relative to the level includes focusing the microscope so that the focal plane of the microscope is offset by 20 microns to 100 microns relative to the level on which at least some cells that are part of the sample are at least partially located.

[0042] In some applications, focusing the microscope so that the focal plane of the microscope is offset relative to the level includes focusing the microscope so that the focal plane of the microscope is offset by 1 to 5 focal depths of the microscope relative to a level on which at least some cells that are part of the sample are at least partially located.

[0043] In some applications, the method further includes sedimenting some cells in the sample to form a monolayer at the monolayer focal level, and focusing the microscope so that the focal plane of the microscope is offset relative to the level includes focusing the microscope so that the focal plane of the microscope is offset relative to the monolayer focal level.

[0044] In some applications, the method further includes allowing some cells in the sample to settle to form a monolayer at the monolayer focal level, and other cells in the sample are suspended in at least one additional level in the sample, and focusing the microscope so that the focal plane of the microscope is offset relative to the level includes focusing the microscope so that the focal plane of the microscope is offset relative to the additional level in which the other cells in the sample are suspended.

[0045] In some applications, determining a property of the portion of the sample based at least in part on the off-focus image includes normalizing the off-focus image to another image and determining a property of the portion of the sample based at least in part on the normalization.

[0046] In some applications, the sample includes a blood sample, and determining a characteristic of a portion of the sample based at least in part on the off-focus image includes identifying one or more entities within the blood sample based at least in part on the off-focus image, wherein the one or more entities are selected from the group consisting of platelets, leukocytes, lymphocytes, granulocytes, monocytes, neutrophils, striped neutrophils, eosinophils, basophils, and macrophages.

[0047] In some applications, the sample includes a blood sample, and determining a characteristic of a portion of the sample based at least in part on the off-focus image includes identifying blast cells within the blood sample based at least in part on the off-focus image.

[0048] In some applications, determining a characteristic of a portion of the sample based at least in part on the off-focus image includes identifying a contour of one or more entities within the sample based at least in part on the off-focus image.

[0049] In some applications, determining a characteristic of a portion of the sample based at least in part on the off-focus image further includes estimating parameters of one or more entities based at least in part on the identified contour, the parameters being selected from the group consisting of cell area and cell volume.

[0050] In some applications, determining a characteristic of a portion of the sample based at least in part on the off-focus image further includes estimating a parameter of the sample based at least in part on the identified contour, wherein the at least one parameter is selected from the group consisting of an average cell area and an average cell volume.

[0051] Further, in accordance with some applications of the present invention, there is provided an apparatus for use with a bodily sample containing cells, the apparatus comprising: A microscope and 1. A computer processor comprising: focusing the microscope so that the focal plane of the microscope is offset relative to a level at which at least some cells that are part of the sample are at least partially located; Drive the microscope to acquire at least one off-focus microscope image of the sample with the focal plane of the microscope offset relative to the level; performing one or more operations selected from the group consisting of identifying entities located within the level based at least in part on the off-focus image, determining contours of entities located within the level, determining parameters of entities located within the level, determining parameters of samples, and any combination thereof; a computer processor configured to: Equipped with.

[0052] Further, in accordance with some applications of the present invention, there is provided a method for use with a bodily sample containing cells, the method comprising: focusing the microscope so that the focal plane of the microscope is at least approximately coincident with a level at which at least some cells that are part of the sample are at least partially disposed; acquiring at least one on-focus microscope image of the sample with the focal plane of the microscope approximately level; focusing the microscope so that the focal plane of the microscope is offset relative to the level; acquiring at least one off-focus microscope image of the sample with the focal plane of the microscope offset relative to the level by a predetermined offset; verifying that the focal plane of the microscope is level in the on-focus image by analyzing the on-focus image and the off-focus image; Includes:

[0053] Further, in accordance with some applications of the present invention, there is provided an apparatus for use with a bodily sample containing cells, the apparatus comprising: A microscope and 1. A computer processor comprising: focusing the microscope so that the focal plane of the microscope is at least approximately coincident with a level at which at least some cells that are part of the sample are at least partially disposed; With the microscope focal plane approximately level, drive the microscope to acquire at least one on-focus microscope image of the sample. Focus the microscope so that the focal plane of the microscope is offset relative to the level. driving the microscope to acquire at least one off-focus microscope image of the sample with the focal plane of the microscope offset by a predetermined offset relative to the level; Verify that the focal plane of the microscope is level in the on-focus image by analyzing the on-focus and off-focus images; a computer processor configured to: Equipped with.

[0054] Further, in accordance with some applications of the present invention, a method is provided for use with a blood sample, the method comprising: identifying NRBC / leukocyte candidates within one or more microscopic images of the blood sample based on the NRBC / leukocyte candidates having characteristics indicative of the likelihood of being either NRBCs or leukocytes; Identifying NRBC / leukocyte candidates in a microscopic image acquired under illumination with light within the wavelength range of 400 nm to 450 nm and / or 500 nm to 600 nm; classifying the NRBC / leukocyte candidates as either NRBCs or leukocytes based at least in part on the level of light absorption by the NRBC / leukocyte candidates in a microscopic image obtained under illumination with light within a wavelength range of 400 nm to 450 nm and / or 500 nm to 600 nm; generating an output based at least in part on the classification of the NRBC / leukocyte candidates into NRBCs or leukocytes; Includes.

[0055] In some applications, Identifying NRBC / white blood cell candidates within a microscopic image acquired under illumination with light within a wavelength range of 400 nm to 450 nm and / or 500 nm to 600 nm includes identifying NRBC / white blood cell candidates within a violet microscopic image acquired under illumination with violet light within a wavelength range of 400 nm to 450 nm; Classifying the NRBC / leukocyte candidates as either NRBCs or leukocytes includes classifying the NRBC / leukocyte candidates as either NRBCs or leukocytes based at least in part on the level of light absorption by the NRBC / leukocyte candidates in a violet microscope image acquired under illumination with light within a wavelength range of 400 nm to 450 nm.

[0056] In some applications, classifying NRBC / leukocyte candidates as either NRBCs or leukocytes includes applying an intensity threshold to the violet microscope image and classifying the NRBC / leukocyte candidates as leukocytes based on the candidate's intensity exceeding the threshold.

[0057] In some applications, the method further includes, in response to detecting the NRBC / white blood cell candidates, selecting to acquire a violet microscope image of the imaging field in which the NRBC / white blood cell candidates are present.

[0058] In some applications, classifying the NRBC / leukocyte candidates as either NRBCs or leukocytes further includes analyzing one or more additional features of the candidates selected from the group consisting of: candidate size, candidate nucleus size, candidate intensity in the fluorescence image, candidate cytoplasm intensity, candidate cytoplasm area, candidate ellipticity, candidate nucleus ellipticity, candidate nucleus circularity, and combinations thereof.

[0059] In some applications, the method further includes adjusting a detection threshold for detecting NRBC in the blood sample in response to the concentration of NRBC detected in the blood sample exceeding the threshold to increase the sensitivity of NRBC detection.

[0060] In some applications, the method further includes adjusting a detection threshold for detecting one or more entities other than NRBC in the blood sample in response to the concentration of NRBC detected in the blood sample exceeding the threshold.

[0061] In some applications, the method further includes reanalyzing at least some of the NRBC / white blood cell candidates in response to the concentration of NRBC detected in the blood sample exceeding a first threshold and the white blood cell count in the sample being less than a second threshold.

[0062] In some applications, the method further includes generating an output indicating that the NRBC count may be erroneous in response to the concentration of NRBC detected in the blood sample exceeding a first threshold and the white blood cell count in the sample being less than a second threshold.

[0063] For some applications, the method further includes generating an output indicating that the white blood cell count may be erroneous in response to the concentration of NRBC detected in the blood sample exceeding a first threshold and the white blood cell count in the sample being less than a second threshold.

[0064] In some applications, the method further includes, in response to the concentration of NRBC detected in the blood sample exceeding a first threshold and the count of a given type of white blood cell in the sample being less than a second threshold, generating an output indicating that the count of a given type of white blood cell may be erroneous.

[0065] Further, in accordance with some applications of the present invention, there is provided an apparatus for use with a blood sample, the apparatus comprising: a microscope configured to acquire a microscopic image of the blood sample; 1. A computer processor comprising: identifying the NRBC / leukocyte candidates within one or more of the microscopic images of the blood sample based on the NRBC / leukocyte candidates having characteristics indicative of the likelihood of being either NRBCs or leukocytes; Identifying NRBC / leukocyte candidates in a microscopic image acquired under illumination with light within the wavelength range of 400 nm to 450 nm and / or 500 nm to 600 nm; classifying the NRBC / leukocyte candidates as either NRBCs or leukocytes based at least in part on the level of light absorption by the NRBC / leukocyte candidates in microscopic images obtained under illumination with light within wavelength ranges of 400 nm to 450 nm and / or 500 nm to 600 nm; generating an output based at least in part on the classification of the NRBC / leukocyte candidates into NRBCs or leukocytes; a computer processor configured to: Equipped with.

[0066] Thus, according to some applications of the present invention, a method is provided for use with a blood sample, the method comprising: identifying NRBC / leukocyte candidates within one or more microscopic images of the blood sample based on the NRBC / leukocyte candidates having characteristics indicative of the likelihood of being either NRBCs or leukocytes; Identifying NRBC / leukocyte candidates in a violet microscope image acquired under illumination with violet light in the wavelength range of 400 nm to 450 nm; classifying the NRBC / leukocyte candidates as either NRBCs or leukocytes based at least in part on the level of light absorption by the NRBC / leukocyte candidates in the violet microscope image; generating an output based at least in part on the classification of the NRBC / leukocyte candidates into NRBCs or leukocytes; Includes:

[0067] In some applications, classifying the NRBC / leukocyte candidates as either NRBCs or leukocytes includes applying an intensity threshold to the violet microscope image and classifying the NRBC / leukocyte candidates as leukocytes based on the candidate's intensity exceeding the threshold.

[0068] For some applications, the method further includes, in response to detecting the NRBC / white blood cell candidates, selecting to acquire a violet microscope image of the imaging field in which the NRBC / white blood cell candidates are present.

[0069] In some applications, classifying the NRBC / white blood cell candidates as either NRBCs or white blood cells further includes analyzing one or more additional features of the candidates selected from the group consisting of: size of the candidate, size of the candidate's nucleus, intensity of the candidate in the fluorescence image, intensity of the candidate's cytoplasm, area of ​​the candidate's cytoplasm, ellipticity of the candidate, ellipticity of the candidate's nucleus, circularity of the candidate's nucleus, and combinations thereof.

[0070] In some applications, the method further includes adjusting a detection threshold for detecting NRBC in the blood sample in response to the concentration of NRBC detected in the blood sample exceeding the threshold to increase the sensitivity of NRBC detection.

[0071] In some applications, the method further includes adjusting a detection threshold for detecting one or more entities other than NRBC in the blood sample in response to the concentration of NRBC detected in the blood sample exceeding the threshold.

[0072] In some applications, the method further includes reanalyzing at least some of the NRBC / white blood cell candidates in response to the concentration of NRBC detected in the blood sample being above a first threshold and the white blood cell count in the sample being below a second threshold.

[0073] For some applications, the method further includes generating an output indicating that the NRBC count may be erroneous in response to the concentration of NRBC detected in the blood sample exceeding a first threshold and the white blood cell count in the sample being less than a second threshold.

[0074] For some applications, the method further includes, in response to a concentration of NRBC detected in the blood sample exceeding a first threshold and a white blood cell count in the sample being less than a second threshold, generating an output indicating that the white blood cell count may be erroneous.

[0075] For some applications, the method further includes, in response to the concentration of NRBC detected in the blood sample exceeding a first threshold and the count of the given type of white blood cell in the sample being less than a second threshold, generating an output indicating that the count of the given type of white blood cell may be erroneous.

[0076] According to some applications of the present invention, there is further provided a method for use with a blood sample, the method comprising: acquiring at least one violet microscope image of the sample under illumination of the sample with violet light in the wavelength range of 400 nm to 450 nm; identifying red blood cells in at least one violet microscope image of the sample; determining a statistical hemoglobin-related characteristic of the sample based on identified red blood cells in at least one violet microscope image of the sample; generating an output based at least in part on the determined statistical hemoglobin-related characteristic of the sample; Includes:

[0077] Further, in accordance with some applications of the present invention, a method is provided for use with a blood sample, the method comprising: identifying NRBC / leukocyte candidates within one or more microscopic images of the blood sample based on the NRBC / leukocyte candidates having characteristics indicative of the likelihood of being either NRBCs or leukocytes; Identifying NRBC / leukocyte candidates in a microscopic image acquired under illumination with light in the wavelength range of 500 nm to 600 nm; classifying the NRBC / leukocyte candidates as either NRBCs or leukocytes based at least in part on the level of light absorption by the NRBC / leukocyte candidates in the microscopic image; generating an output based at least in part on the classification of the NRBC / leukocyte candidates into NRBCs or leukocytes; Includes:

[0078] Further, in accordance with some applications of the present invention, a method is provided for use with a blood sample, the method comprising: acquiring at least one microscopic image of the sample under illumination of the sample with light in the wavelength range of 500 nm to 600 nm; identifying red blood cells in at least one microscopic image of the sample; determining a statistical hemoglobin-related characteristic of the sample based on identified red blood cells in at least one microscopic image of the sample; generating an output based at least in part on the determined statistical hemoglobin-related characteristic of the sample; Includes.

[0079] The present invention will be more fully understood from the following detailed description of the embodiments when considered in conjunction with the drawings. [Brief explanation of the drawings]

[0080] [Figure 1] 1 is a block diagram illustrating components of a biological sample analysis system according to some applications of the present invention. [Figure 2A] 1 is a schematic diagram of an optical measurement unit according to some applications of the present invention; [Figure 2B] 1 is a schematic diagram of an optical measurement unit according to some applications of the present invention; [Figure 2C] 1 is a schematic diagram of an optical measurement unit according to some applications of the present invention; [Figure 3A] 1A-1C are schematic diagrams of various views of a sample carrier used to perform both microscopic and optical density measurements in accordance with some applications of the present invention. [Figure 3B] 1A-1C are schematic diagrams of various views of a sample carrier used to perform both microscopic and optical density measurements in accordance with some applications of the present invention. [Figure 3C] 1A-1C are schematic diagrams of various views of a sample carrier used to perform both microscopic and optical density measurements in accordance with some applications of the present invention. [Figure 4A] 1 is a microscopic image of an entity that is a NRBC / leukocyte candidate, according to some applications of the present invention. [Figure 4B] 1 is a microscopic image of NRBCs acquired under violet illumination conditions, in accordance with some applications of the present invention. [Figure 4C] 1 is a microscopic image of white blood cells acquired under violet lighting conditions, in accordance with some applications of the present invention. [Figure 5] 1 is a flowchart illustrating method steps performed on NRBC / leukocyte candidates identified in one or more microscopic images of a blood sample, according to some applications of the present invention. [Figure 6A] 1 is a microscopic image of red blood cells acquired under red lighting conditions, in accordance with some applications of the present invention. [Figure 6B] 1 is a microscopic image of red blood cells acquired under green illumination conditions, in accordance with some applications of the present invention. [Figure 6C] 1 is a microscopic image of red blood cells acquired under violet lighting conditions, in accordance with some applications of the present invention. [Figure 7] 1 is a flowchart illustrating method steps performed on red blood cells identified in one or more microscopic images of a blood sample, according to some applications of the present invention. [Figure 8] 1 is a flow chart illustrating steps of a method for use with a body sample containing cells, according to some applications of the present invention. [Figure 9A] 1 is an example of a bright field microscope image of a cell monolayer of a blood sample acquired using violet illumination with the microscope focal plane set to coincide with the cell monolayer, according to some applications of the present invention. [Figure 9B] 1 is an example of a bright field microscope image of a cell monolayer of a blood sample acquired using violet illumination with the microscope focal plane set off-focus relative to the cell monolayer, according to some applications of the present invention. [Figure 9C]9A and 9B are fluorescence microscope images of the same sample sections shown in FIGS. 9A and 9B after the samples have been stained with acridine orange and Hoechst reagent and excited with UV light to cause platelets to fluoresce, according to some applications of the present invention. [Figure 10A] 1 is an example of a bright field microscope image of a cell monolayer of a blood sample acquired using violet illumination with the microscope focal plane set to coincide with the cell monolayer, according to some applications of the present invention. [Figure 10B] 1 is an example of a bright field microscope image of a cell monolayer of a blood sample acquired using violet illumination with the microscope focal plane set off-focus relative to the cell monolayer, according to some applications of the present invention. [Figure 11A] 1 is an example of a bright field microscope image of a cell monolayer of a blood sample acquired using green illumination with the microscope focal plane set to coincide with the cell monolayer, according to some applications of the present invention. [Figure 11B] 1 is an example of a bright field microscope image of a cell monolayer of a blood sample acquired using green illumination with the microscope focal plane set to be off-focus with respect to the cell monolayer, in accordance with some applications of the present invention. [Figure 12A] 1 is an example of a bright field microscope image of a cell monolayer of a blood sample acquired using green illumination with the microscope focal plane set to coincide with the cell monolayer, according to some applications of the present invention. [Figure 12B] 1 is an example of a bright field microscope image of a cell monolayer of a blood sample acquired using green illumination with the microscope focal plane set off-focus relative to the cell monolayer, according to some applications of the present invention. [Figure 12C] 1 is an example of a bright field microscope image of a cell monolayer of a blood sample acquired using green illumination with the microscope focal plane set to be off-focus with respect to the cell monolayer, in accordance with some applications of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0081] Reference is now made to FIG. 1A, a block diagram illustrating components of a biological sample analysis system 20 according to some applications of the present invention. Typically, a biological sample (e.g., a blood sample) is placed in a sample carrier 22. While the sample is 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 may include a microscope (e.g., a digital microscope), a spectrophotometer, a photometer, a spectrometer, a camera, a spectral camera, a hyperspectral camera, a fluorometer, a fluorescence spectrometer, and / or a photodetector (e.g., a photodiode, a photoresistor, and / or a phototransistor). In some applications, the optical measurement devices include a dedicated light source (e.g., a light-emitting diode, an incandescent light source, etc.) and / or optical elements (e.g., lenses, diffusers, filters, etc.) for collecting and / or manipulating light emission.

[0082] Typically, a computer processor 28 receives and processes optical measurements performed by the optical measurement devices. More typically, the computer processor controls the acquisition of optical measurements performed by one or more optical measurement devices. The computer processor communicates with memory 30. A user (e.g., a laboratory technician or an individual from whom a sample was taken) sends instructions to the computer processor via a user interface 32. In some applications, the user interface includes a keyboard, a mouse, a joystick, a touchscreen device (such as a smartphone or 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 output via an output device 34. More typically, the output device includes a display, such as a monitor, and the output includes output displayed on the display. In some applications, the processor generates output on different types of visual, textual, graphical, tactile, auditory, and / or video output devices, such as speakers, headphones, a smartphone, or a tablet computer. In some applications, the user interface 32 functions as both an input interface and an output interface, i.e., an input / output interface. In some applications, the processor generates 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 output on a printer.

[0083] Reference is now made to FIGS. 2A, 2B, and 2C, which are schematic diagrams of an optical measurement unit 31 according to some applications of the present invention. FIG. 2A shows a perspective view of the exterior of the fully assembled device, and FIGS. 2B and 2C show perspective views of the device with a transparent cover to reveal the internal components of the device. In some applications, one or more optical measurement devices 24 (and / or a computer processor 28 and memory 30) are housed within the optical measurement unit 31. A sample carrier 22 is positioned within the optical measurement unit to perform optical measurements on the sample. For example, the optical measurement unit can define a slot 36 through which the sample carrier is inserted into the optical measurement unit. Typically, the optical measurement unit includes a stage 64 configured to support the sample carrier 22 within the optical measurement unit. In some applications, a screen 63 on the cover of the optical measurement unit (e.g., a screen on the front cover of the illustrated optical measurement unit) serves as the user interface 32 and / or the output device 34.

[0084] Typically, the optical measurement unit includes a microscope system 37 (illustrated in FIGS. 2B-2C) configured to perform microscopic imaging of a portion of the sample. For some applications, the microscope system includes a light source set 65 (typically including a set of bright-field light sources (e.g., light-emitting diodes) configured to be used for bright-field imaging of the sample and a set of fluorescent light sources (e.g., light-emitting diodes) configured to be used for fluorescent 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 39 (illustrated in FIG. 2C) configured to perform optical density measurements (e.g., optical absorption measurements) 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 photodetectors configured to perform optical density measurements on the sample. In some applications, each of the aforementioned light source sets (i.e., the bright field light source set, the fluorescence light source set, and the optical density measurement light source set) includes multiple light sources (e.g., multiple light emitting diodes), each configured to emit light at a respective wavelength or in a respective wavelength band.

[0085] Reference is now made to FIGS. 3A and 3B, which are schematic illustrations of views of a sample carrier 22 according to some applications of the present invention. FIG. 3A is a top view of the sample carrier (for illustrative purposes, the top cover of the sample carrier is shown as opaque in FIG. 3A), and FIG. 3B is a bottom view (the sample carrier is rotated about a short edge relative to the view shown in FIG. 3A). Typically, the sample carrier includes a first set 52 of one or more sample chambers used to perform microscopic analysis on the sample and a second set 54 of sample chambers used to perform optical density measurements on the sample. Typically, the sample chambers of the sample carrier are filled with a body sample, such as blood, via a sample inlet aperture 38. In some applications, the sample chambers define one or more outlet apertures 40. The outlet apertures are configured to facilitate filling of the sample chambers with a body sample by releasing air present in the sample chamber from the sample chamber. Typically, as shown, the outlet apertures are located longitudinally opposite (with respect to the sample chambers of the sample carrier) from the inlet apertures. In some applications, the outlet holes thereby provide a more efficient air relief mechanism than if they were located closer to the inlet holes.

[0086] Refer to FIG. 3C, which shows an exploded view of sample carrier 22 according to some applications of the present invention. In some applications, the sample carrier includes at least three components: a molding component 42, a glass layer 44 (e.g., a glass sheet), and an adhesive layer 46 configured to attach the glass layer to the underside of the molding component. The molding component is typically made of a polymer (e.g., plastic) that is molded (e.g., by injection molding) to provide chambers with desired geometries. For example, as shown, the molding component is typically molded to define inlet holes 38, outlet holes 40, and a groove 48 surrounding the center of each sample chamber. The groove typically facilitates filling of the sample chambers with a body sample by directing air to the outlet holes and / or directing the body sample to flow around the center of the sample chamber.

[0087] In some applications, a sample carrier such as that shown in FIGS. 3A-3C is used when performing a complete blood count on a blood sample. In some such applications, the sample carrier is used with an optical measurement unit 31 configured as generally shown and described with reference to FIGS. 2A-2C. In some applications, a first portion of the blood sample is placed in a first set of sample chambers 52 (e.g., used to perform a microscopic analysis on the sample using a microscope system 37 (shown in FIGS. 2B-2C)) and a second portion of the blood sample is placed in a second set of sample chambers 54 (e.g., used to perform an optical density measurement on the sample using an optical density measurement unit 39 (shown in FIG. 2C)). In some applications, as shown, the first set of sample chambers 52 includes multiple sample chambers and the second set of sample chambers 54 includes only one sample chamber. However, the scope of the present invention includes the use of any number of sample chambers (e.g., a single sample chamber or multiple sample chambers) in either the first set of sample chambers or the second set of sample chambers, 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 may include a pH buffer, a dye, a fluorescent dye, an antibody, a sphering agent, a lysing agent, etc. Typically, the second portion of the blood sample placed in the second set of sample chambers 54 is a native, undiluted blood sample. Alternatively or additionally, the second portion of the blood sample may be a sample that has been altered in some way, including, for example, one or more of dilution (e.g., dilution in a controlled manner), addition of a component or reagent, or fractionation.

[0088] In some applications, a first portion of the blood sample (disposed in the first set of chambers 52) is stained with one or more staining substances before the sample is imaged under a microscope. For example, the staining substance may be configured to preferentially stain DNA over other cellular components. Alternatively, the staining substance may be configured to preferentially stain all cellular nucleic acids over other cellular components. For example, the sample may be stained with acridine orange reagent, Hoechst reagent, and / or any other staining substance configured to preferentially stain DNA and / or RNA in a blood sample. Optionally, the staining substance is configured to stain all cellular nucleic acids, but under certain lighting and filter conditions, the respective staining of DNA and RNA may be more prominently visible, as is known for acridine orange, for example. Images of the sample may be acquired using imaging conditions that allow for cell detection (e.g., bright field) and / or visualization of the stained portions (e.g., appropriate fluorescent illumination). Typically, the first portion of the sample is stained with acridine orange and Hoechst reagent. For example, a first (diluted) portion of a blood sample may be prepared using techniques such as those described in U.S. Pat. No. 9,329,129 to Pollak (incorporated herein by reference). U.S. Pat. No. 9,329,129 describes a method of preparing a blood sample for analysis, including a dilution step that facilitates identification and / or counting of components in a microscopic image of the sample. In some applications, the first portion of the sample is stained with one or more dyes that visualize platelets in the sample under bright-field imaging conditions and / or fluorescent imaging conditions, e.g., as described above. For example, the first portion of the sample may be stained with methylene blue and / or Romanowsky stain.

[0089] Referring again to FIGS. 2B-2C , typically, the sample carrier 22 is supported by a stage 64 within the optical measurement unit. More typically, the stage has a forked design, so that the sample carrier is supported around its edges by the stage but does not obstruct the visibility of the sample chamber of the sample carrier by the optical measurement device. In some applications, the sample carrier is held within the stage such that the shaping component 42 of the sample carrier is positioned above the glass layer 44, and the objective 66 of the microscope unit of the optical measurement unit is positioned below the glass layer of the sample carrier. Typically, at least some light sources 65 used during microscopy measurements performed on the sample (e.g., light sources used during bright-field imaging) illuminate the sample carrier from above the shaping component. More typically, at least some additional light sources (not shown) illuminate the sample carrier from below (e.g., via the objective). For example, a light source used to excite the sample during fluorescence microscopy can illuminate the sample carrier from below (e.g., via the objective).

[0090] Typically, prior to imaging with a microscope, a first portion of the blood (disposed in the first set of sample chambers 52) is allowed to settle to form a monolayer of cells, using techniques such as those described in U.S. Pat. No. 9,329,129 to Pollak (incorporated herein by reference). In some applications, the first portion of the blood is a cell suspension, and each chamber in the first set of chambers 52 defines a cavity 55 including a base surface 57 (shown in FIG. 3C). Typically, cells in the cell suspension are allowed to settle on the base surfaces of the sample chambers of the carrier to form a monolayer of cells on the base surfaces of the sample chambers. After allowing the cells to settle on the base surfaces of the sample chambers (e.g., by allowing them to settle for a predetermined time period), at least one microscope image of at least a portion of the monolayer of cells is typically acquired. Typically, multiple images of the monolayer are acquired, each corresponding to an imaging field located in a different area within the imaging plane of the monolayer. Typically, the optimal depth level at which to focus the microscope to image the monolayer is determined using techniques such as those described in U.S. Patent No. 10,176,565 to Greenfield, which is incorporated herein by reference. In some applications, each imaging field has a different optimal depth level.

[0091] It should be noted that, in the context of this application, the term monolayer is used to refer to a layer of cells that have settled so as to be located within a single focal level of a microscope (referred to herein as the "monolayer focal level"). There may be some overlap of cells within the monolayer, e.g., there may be two or more overlapping layers of cells in a particular area. For example, red blood cells may overlap each other within the monolayer, and / or platelets may overlap or reside on red blood cells within the monolayer.

[0092] In some applications, microscopic analysis of a first portion of a blood sample is performed on a 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, typically emitting in respective spectral bands). More typically, the first portion of the blood sample is also imaged under fluorescence imaging. Typically, fluorescence imaging is performed by directing light of known excitation wavelengths (i.e., wavelengths at which the stained objects (i.e., objects that have absorbed one or more dyes) are known to emit fluorescent light when excited with light of these wavelengths) toward the sample to excite stained objects in the sample, and detecting the fluorescent light. Typically, fluorescence imaging involves illuminating the sample with known excitation wavelengths using a separate set of light sources (e.g., one or more light-emitting diodes).

[0093] As described with reference to U.S. Patent Application Publication No. US 2019 / 0302099 to Pollak (incorporated herein by reference), in some applications, sample chambers belonging to set 52 (used for microscopic measurements) have different heights from one another. The purpose of this is to facilitate measurement of different measurands using microscopic images of each sample chamber and / or to use different sample chambers for microscopic analysis of each sample type. For example, if a blood sample and / or the monolayer formed by the sample has a relatively low density of red blood cells, performing the measurement in a sample chamber of a sample carrier with a larger height (i.e., a sample chamber of a sample carrier with a larger height compared to a different sample chamber with a smaller height) can ensure a sufficient density of cells is present and / or a sufficient density of cells is present in the monolayer formed by the sample to provide statistically reliable data. Such measurements may include, for example, measuring the density of red blood cells, other cellular attributes (e.g., the number of abnormal red blood cells, the number of red blood cells containing intracellular bodies (e.g., pathogens, Howell-Jolly bodies), etc.), and / or hemoglobin concentration. Conversely, if the blood sample and / or the monolayer formed by the sample has a relatively high density of red blood cells, performing such measurements in chambers of the sample carrier with a relatively small height may, for example, ensure that there is sufficient sparsity of cells and / or that there are sufficient sparse cells within the monolayer of cells formed by the sample to identify the cells in the microscope image. In some applications, such methods are performed even if the height difference between the chambers in set 52 is not precisely known.

[0094] In some applications, the sample chamber in the sample carrier in which the optical measurement is performed is selected based on the measurand being measured. For example, a sample chamber in a sample carrier with a large height can be used to perform white blood cell counting (e.g., to reduce statistical errors that may arise from low counts in shallow areas), white blood cell differentiation, and / or detection of rare white blood cell morphologies. Conversely, microscopic images can be acquired from a sample chamber in a sample carrier with a relatively small height to determine mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), red blood cell distribution width (RDW), red blood cell morphological characteristics, and / or red blood cell abnormalities. This is because in such sample chambers, cells are relatively sparsely distributed within the area of ​​the region and / or form a relatively sparsely distributed monolayer. Similarly, microscopic images can be acquired from a sample chamber in a sample carrier with a relatively small height to perform platelet counting, platelet classification, and / or extraction of any other platelet attributes (e.g., volume). This is because in such a sample chamber there are fewer red blood cells that overlap (fully or partially) with the platelets in the microscopic image and / or in the monolayer.

[0095] According to the above example, it may be preferable to use a sample chamber of a sample carrier with a small height to perform optical measurements to measure one measurand in a sample (e.g., a blood sample), while it may be preferable to use a sample chamber of a sample carrier with a large height to perform optical measurements to measure another measurand in such a sample. Thus, in some applications, a first measurand in a sample is measured by performing a first optical measurement on a portion of the sample disposed in a first sample chamber of a set of sample carriers 52 (e.g., by acquiring a microscopic image of the portion), and a second measurand of the same sample is measured by performing a second optical measurement on a portion of the sample disposed in a second sample chamber of the set of sample carriers 52 (e.g., by acquiring a microscopic image of the portion). In some applications, the first and second measurands are normalized relative to each other, for example, using techniques such as those described in U.S. Patent Application Publication No. US2019 / 0145963 to Zait, which is incorporated herein by reference.

[0096] Typically, 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 was performed. Typically, the optical density measurement is performed on a second portion of the sample (typically placed in undiluted form within the second set of sample chambers 54). For example, optical absorption, transmittance, fluorescence, and / or luminescence measurements can be performed on the sample to determine the concentration and / or density of components.

[0097] Referring again to FIG. 3B , in some applications, a sample chamber (used for optical density measurements) belonging to set 54 typically defines at least a first region 56 (typically deep) and a second region 58 (typically shallow). The heights of the sample chambers in the first and second regions are different as specified. This is described, for example, in U.S. Patent Application Publication No. US2019 / 0302099 to Pollak, which is incorporated herein by reference. The heights of the first and second regions 56 and 58 of the sample chamber are defined by a lower surface defined by the glass layer and an upper surface defined by the molding component. The upper surface of the second region is stepped relative to the upper surface of the first region. The step between the top surfaces of the first and second regions provides a predetermined height difference Δh between these regions, so that even if the absolute heights of these 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 determine parameters of the sample using techniques such as those described herein and in U.S. Patent Application Publication No. US2019 / 0302099 to Pollak, which is incorporated herein by reference. In some applications, the height of the sample chamber varies from first region 56 to second region 58 and again from second region 58 to third region 59, such that along the sample chamber, first region 56 defines a maximum height region, second region 58 defines an intermediate height region, and third region 59 defines a minimum height region. In some applications, there are additional height variations along the length of the sample chamber and / or there is a gradual variation in height along the length of the sample chamber.

[0098] As described above, optical measurements are performed on the sample using one or more optical measurement devices 24 while the sample is disposed on the sample carrier. Typically, the sample is interrogated by the optical measurement device through a glass layer. The glass is transparent, at least to the wavelengths typically used by the optical measurement device. Typically, while performing the optical measurements, the sample carrier is inserted into an optical measurement unit 31 housing the optical measurement device. Typically, the optical measurement unit houses the sample carrier such that a molding layer is disposed above the glass layer and the optical measurement unit is disposed below the glass layer of the sample carrier so that the optical measurement unit can perform optical measurements on the sample through the glass layer. The sample carrier is formed by attaching a glass layer to a molding component. For example, the glass layer and molding component can be bonded to each other during manufacturing or assembly (e.g., using thermal bonding, solvent bonding, ultrasonic welding, laser welding, heat staking, adhesives, mechanical clamps, and / or additional substrates). In some applications, the glass layer and molding component are bonded to each other during manufacturing or assembly using an adhesive layer 46.

[0099] Reference is now made to Figures 4A through 4C, which are microscopy images acquired in accordance with several application examples of the present invention. As mentioned in the Background section, mammalian red blood cells are the oxygen carriers of the body. During the maturation process, red blood cells undergo enucleation, i.e., the nucleus is completely removed from the cell. Normally, nucleated red blood cells (NRBCs) are not detectable in the peripheral blood of adult patients. However, in some conditions (e.g., newborns, cancer patients, and anemia patients), NRBCs are detectable in peripheral blood. Because NRBCs are similar in size and nuclear content to some white blood cells (especially lymphocytes), it is usually difficult to distinguish them from white blood cells. For example, Figure 4A shows a composite image in which a fluorescent microscopy image is superimposed on a brightfield microscopy image. The brightfield image was acquired under violet illumination conditions, and the microscope was off-focus on the cell monolayer within the sample when acquiring the brightfield image. The sample was stained with Hoechst reagent, which has an affinity for DNA, and the Hoechst reagent was excited before acquiring the fluorescent image. (As noted above, additional brightfield and / or fluorescent images of the sample are typically acquired; for example, the sample is typically stained with acridine orange and a fluorescent image is acquired in which the acridine orange is excited.) Entity 60 is visible in the image, and the size of this entity indicates that it may be either an NRBC or a white blood cell. Furthermore, the center of this entity fluoresces, indicating the presence of a nucleus, which would be expected if the entity were either an NRBC or a white blood cell.

[0100] As noted above, in some applications of the present invention, a complete blood count is performed on a blood sample. In the context of a complete blood count, it is typically important to distinguish between NRBCs and white blood cells to avoid overcounting white blood cells (especially in patients with low white blood cell counts) and to detect the presence of NRBCs, which may indicate an underlying disease.

[0101] According to some applications of the present invention, to distinguish between white blood cells (e.g., lymphocytes) and NRBCs (e.g., in situations where NRBC / white blood cell candidates (i.e., candidates that may be either NRBCs or white blood cells) are detected), microscopic images are acquired while illuminating the sample with light at a wavelength at which hemoglobin has a high level of absorption. Typically, violet light is used, e.g., light having a wavelength greater than 400 nm and / or less than 450 nm (e.g., 400-450 nm). Within this wavelength range, hemoglobin absorption is relatively high compared to other wavelengths in the visible spectrum. Typically, NRBCs have a high hemoglobin content (on the order of 30 picograms per cell), while white blood cells do not contain hemoglobin. Therefore, in images acquired under violet light illumination, NRBCs typically absorb light, whereas white blood cells do not. In some applications, light having a wavelength greater than 500 nm and / or less than 600 nm (e.g., 500-600 nm) is used. Within this wavelength range, carbaminohemoglobin has a relatively high absorption compared to other wavelengths in the visible spectrum, so that in images acquired under illumination within the above wavelength range, NRBCs typically absorb light, whereas white blood cells do not.

[0102] 4B and 4C, FIG. 4B shows NRBCs 62 in an image acquired under violet light illumination, and FIG. 4C shows white blood cells 67 in an image acquired under violet light illumination. As shown, the NRBCs appear dark overall due to the absorption of light by hemoglobin within the NRBCs, while the centers of the white blood cells do not appear dark due to the absence of hemoglobin within the white blood cells. Thus, entities are typically classified as either NRBCs or white blood cells based at least in part on the intensity of the entities in an image acquired under violet light illumination. In some applications, an intensity threshold is applied to the image acquired under violet lighting conditions (and / or to a given region or pixel thereof), and entities are classified as either NRBCs or white blood cells based on whether the intensity of the entities exceeds this threshold.

[0103] Typically, entities that are NRBC / leukocyte candidates (i.e., candidates that may be either NRBCs or leukocytes) are first identified based on bright-field images acquired at wavelengths other than violet wavelengths and / or based on fluorescent images. In response to identifying such candidates, images acquired under violet illumination conditions are analyzed (e.g., using the techniques described above) to distinguish between NRBCs and leukocytes. In some applications, if one or more (e.g., a given minimum number) NRBC / leukocyte candidates are identified within a given imaging field, only images of that imaging field are acquired under violet illumination conditions. That is, the computer processor drives the microscope to acquire images under violet illumination only when it detects the need to do so due to the identification of NRBC / leukocyte candidates (and / or NRBC / leukocyte candidates exceeding a given number or concentration) within the imaging field.

[0104] In some applications, additional features are used to distinguish between NRBCs and white blood cells. For example, such additional features may include cell size, nuclear size, fluorescence intensity, cytoplasmic intensity, cytoplasmic area, cell ellipticity, nuclear ellipticity, nuclear circularity, and / or any combination of the above features. In some applications, one or more images of the NRBC / white blood cell candidates are acquired under different bright-field illumination conditions, such as red and / or green light, and the one or more additional images are analyzed to verify the classification of the candidates. In some applications, the image acquired under violet illumination conditions and / or the one or more additional images are off-focus bright-field images. In some applications, a machine learning classifier (e.g., a convolutional neural network classifier, a decision tree classifier, a regression analysis classifier, a Bayesian network classifier, and / or a support network vector classifier) ​​is applied to one or more of the above features of the NRBC / white blood cell candidates to classify them as either NRBCs or white blood cells. Alternatively or additionally, a neural network classifier is applied to the original images (such images typically include images acquired under violet lighting conditions) to classify NRBC / leukocyte candidates as either NRBC or leukocyte.

[0105] As mentioned above, NRBCs are not normally present in the blood of healthy adults, so the presence of NRBCs indicates an underlying clinical condition. The presence of one or more NRBCs in a subject's blood may indicate that another entity in the blood sample is likely to be an NRBC, rather than a white blood cell (which is always present in blood). In some applications, in response to detecting even one NRBC (and / or in response to detecting a given number or concentration of NRBCs), one or more thresholds used to identify an entity as an NRBC are adjusted to increase the sensitivity of the computer processor to NRBCs. Typically, in response to identifying one or more NRBCs (e.g., in response to identifying more than a given number and / or more than a given concentration of NRBCs), an output is generated to the user notifying them that NRBCs have been identified and / or indicating the concentration or relative concentration of the identified NRBCs.

[0106] In some applications, in response to detecting more than a given number and / or more than a given concentration of NRBCs, the computer processor adjusts the threshold used to detect other entities and / or generates an output indicating that the counts of the other entities may be erroneous. In some applications, in response to detecting a relatively high count of NRBCs along with a relatively low count of white blood cells, the computer processor interprets this as an indication that some NRBC / white blood cell candidates have been misclassified. In response, the computer processor typically reanalyzes at least some of the candidates and / or generates an output indicating that the counts of NRBCs and / or white blood cells may be erroneous. In some applications, the computer processor detects that only one given type (or types) of white blood cells have a low concentration, indicating that this type (or types) of white blood cells have been erroneously differentiated from NRBCs. In response, the computer processor typically generates an output indicating that the counts of this given type (or types) of white blood cells may be erroneous.

[0107] Reference is now made to Figure 5, a flowchart illustrating method steps performed on NRBC / leukocyte candidates identified in one or more microscopic images of a blood sample, in accordance with some applications of the present invention. As described above with reference to Figures 4A-4C and illustrated in the flowchart of Figure 5, NRBC / leukocyte candidates are identified in one or more microscopic images of a blood sample (step 100), and then identified in microscopic images acquired under illumination in the 400 nm to 450 nm wavelength range or under illumination with light in the 500 nm to 600 nm wavelength range (step 102). The NRBC / leukocyte candidates are then classified as either NRBC or leukocytes based on the level of light absorption by the NRBC / leukocyte candidates in the microscopic images (step 104), and an output is generated based on the classification of the NRBC / leukocyte candidates as NRBC or leukocytes (step 106).

[0108] Reference is now made to Figures 6A, 6B, and 6C, which are microscopic images of a red blood cell 70 acquired under red, green, and violet illumination conditions, respectively, in accordance with some applications of the present invention. Typically, the absorption of hemoglobin variants in the violet light range (e.g., above 400 nm and / or below 450 nm (e.g., between 400 nm and 450 nm)) is one to three orders of magnitude greater than the absorption at other wavelengths in the visible spectrum. As can be observed in Figures 6A through 6C, the contrast between the red blood cell and the background in Figure 6C is significantly greater than in Figure 6A (acquired under red illumination) and Figure 6B (acquired under green illumination).

[0109] Thus, in some applications, a blood sample is imaged under violet illumination conditions to determine hemoglobin-related properties of the blood sample. For example, by measuring the absorption of violet light, the hemoglobin content of a single red blood cell can be determined. In some applications, the absorption measurements performed under violet illumination conditions are combined with additional absorption measurements performed under different illumination conditions (e.g., red or green illumination conditions). This is typically performed on multiple cells to determine statistical hemoglobin-related properties of the sample, such as mean corpuscular hemoglobin (MCH) and hemoglobin distribution width. In some applications, cell volume data is also determined. For example, the volume of individual cells and / or the mean cell volume of red blood cells in the sample can be determined. Based on the MCH and cell volume data, a computer processor determines the mean corpuscular hemoglobin concentration of the sample. In some applications, light having a wavelength greater than 500 nm and / or less than 600 nm (e.g., 500-600 nm) is used. Within this wavelength range, the absorption of carbaminohemoglobin is relatively high compared to other wavelengths in the visible spectrum.

[0110] In some applications, the red blood cell population is classified into subpopulations, such as reticulocytes, NRBCs, and / or cells with specific morphological characteristics (e.g., sickle cells, oval cells, target cells, sea urchin cells, etc.). In some applications, one of several red blood cell subpopulations determines a statistical hemoglobin-related characteristic of the sample, as described above. For example, the computer processor can determine the mean reticulocyte hemoglobin, or the mean sickle cell hemoglobin, the mean sea urchin hemoglobin concentration, etc.

[0111] Reference is now made to Figure 7, a flowchart illustrating method steps performed on red blood cells identified in one or more microscopic images of a blood sample, according to some applications of the present invention. As described above with reference to Figures 6A-6C and illustrated in the flowchart of Figure 7, a microscopic image of the blood sample is obtained (step 110) under illumination with light in the wavelength range of 400 nm to 450 nm or under illumination with light in the wavelength range of 500 nm to 600 nm, and red blood cells are identified in the microscopic image (step 112). Hemoglobin-related properties of the blood sample are determined based on the identified red blood cells (step 114), and an output is generated based on the determined hemoglobin-related properties (step 116).

[0112] As described above, in some applications, cells in a cell suspension are allowed to settle on the base surface of a sample chamber of the carrier 22 to form a monolayer of cells on the base surface of the sample chamber. After allowing the cells to settle on the base surface of the sample chamber (e.g., by allowing them to settle for a predetermined time period), at least one microscope image of at least a portion of the monolayer of cells is typically acquired. As described above, in the context of this application, the term monolayer is used to refer to a layer of settled cells that is positioned within a single focal level of the microscope (referred to herein as the "monolayer focal level"). In some applications, in addition to acquiring images by setting the microscope focal plane to approximately coincide with the monolayer focal level (such images are referred to herein as "on-focus" images), the microscope also acquires images by setting the microscope focal plane to be offset along the optical axis from the monolayer focal level (such images are referred to herein as "off-focus" images). Typically, such off-focus microscope images are acquired by setting the microscope focal plane closer to the microscope objective lens than the monolayer focus level, although the scope of the present invention also includes acquiring off-focus images by setting the microscope focal plane farther from the microscope objective lens than the monolayer focus level. Typically, the off-focus microscope image is acquired by setting the microscope focal plane at a predetermined offset from the monolayer focus level. In some applications, the off-focus microscope image is acquired by setting the microscope focal plane at an offset of more than 20 microns and / or less than 100 microns, e.g., 20 to 100 microns, from the monolayer focus level. Alternatively or additionally, the off-focus microscope image is acquired by setting the microscope focal plane at an offset of more than 1 times the microscope focal depth and / or less than 5 times the microscope focal depth, e.g., 1 to 5 microscope focal depths, from the monolayer focus level.

[0113] The inventors of the present application have discovered that such off-focus microscopic images can yield important data about a sample. Specifically, off-focus images are typically used to identify cellular contours and / or identify specific entities within a sample. These entities include, for example, white blood cells, white blood cell types (e.g., lymphocytes, granulocytes, monocytes, neutrophils, streaked neutrophils, eosinophils, basophils, macrophages, and / or blast cells), red blood cells, red blood cell types (e.g., mature red blood cells, NRBCs, echinocytes, sickle cells, teardrop cells), and / or platelets. In some applications, off-focus images are used to improve the visibility of such entities relative to other entities, allowing them to be identified with greater certainty. Alternatively or additionally, off-focus images are used to facilitate distinguishing such entities from other entities with which they might otherwise be confused. In some applications, off-focus images are used to show cellular characteristics such as the hemoglobin content of red blood cells, other components of red blood cells, and / or the maturity of the cells (e.g., neutrophils).

[0114] First, refer to FIG. 8, a flowchart illustrating steps of a method for use with a body sample containing cells, according to some applications of the present invention. As described above and illustrated in the flowchart of FIG. 8, a microscope is focused on its "on-focus" focal plane (step 120). At the "on-focus" focal plane, the focal plane of the microscope at least approximately coincides with the level at which at least some cells that are part of the sample are at least partially located. An on-focus microscope image is then acquired (step 122) while the focal plane is "on-focus" and approximately coincides with the level at which at least some cells that are part of the sample are at least partially located. The microscope is then focused on its "off-focus" focal plane (step 124). At the "off-focus" focal plane, the focal plane of the microscope is offset from the level at which at least some cells that are part of the sample are at least partially located (i.e., offset from the "on-focus" focal plane). An off-focus microscope image is then acquired (step 126) while the focal plane of the microscope is offset from the level at which at least some cells that are part of the sample are at least partially located. Then, a property of at least a portion of the sample is determined based at least in part on the on-focus and off-focus images (step 128).

[0115] Typically, off-focus images are acquired not only at wavelengths where hemoglobin has little absorption (e.g., red light, such as light in the wavelength range of about 620-640 nm), but also at wavelengths where hemoglobin has mild absorption (e.g., green light, such as light in the wavelength range of 505-535 nm or 520-530 nm), or at wavelengths where hemoglobin has strong absorption (e.g., violet light, such as light in the wavelength range of more than 400 nm and / or less than 450 nm (e.g., 400-450 nm)). Some examples of the use of such images are described below with reference to Figures 9A-12C.

[0116] Reference is now made to FIGS. 9A and 9B, which are example bright-field microscope images of a cell monolayer of a blood sample acquired using violet illumination, in accordance with some applications of the present invention. These images were acquired with the microscope focal plane set to coincide with the cell monolayer ( FIG. 9A ) and with the microscope focal plane set to be off-focus relative to the cell monolayer ( FIG. 9B ). In the on-focus image ( FIG. 9A ), red blood cells 80 and echinocytes 82 are visible. Additionally, bright areas 84 are observable. These bright areas are platelets. However, it may be difficult to identify platelets based on this raw on-focus image, and it may also be difficult to distinguish platelets from other entities (such as intraerythrocytic parasites or white blood cells). Also, as can be seen, the bright areas are less visible in the off-focus image ( FIG. 9B ). In some applications, a computer processor performs normalization based on the on-focus and off-focus images (e.g., by subtracting one image from the other or by dividing one image by the other). Typically, based on the normalization, the bright areas become more clearly visible, allowing a computer processor to identify the bright areas as platelets with a higher degree of certainty than would be possible based solely on the raw, on-focus image. (Note that in some applications, the two images are not actually normalized to one another, but rather the computer processor performs processing steps equivalent to normalizing the images or portions of the images to one another.) Reference is now made to FIG. 9C , which is a fluorescence microscopy image of the same sample portion shown in FIGS. 9A and 9B after staining the sample with acridine orange and Hoechst reagent to cause platelets to fluoresce and exciting with UV light, in accordance with some applications of the present invention. In this image, the platelets are clearly visible and distinguishable from surrounding entities. Performing normalization based on on-focus and off-focus images, as shown in FIGS. 9A and 9B, is an alternative or additional method for improving platelet visibility.

[0117] Reference is now made to FIGS. 10A and 10B, which are example bright-field microscope images of a cell monolayer of a blood sample acquired using violet illumination, in accordance with some applications of the present invention. These images were acquired, respectively, with the microscope focal plane set to coincide with the cell monolayer ( FIG. 10A ) and with the microscope focal plane set to be off-focus relative to the cell monolayer ( FIG. 10B ). In the on-focus image ( FIG. 10A ), a bright circular entity 90 is visible. This entity is a white blood cell. However, it may be difficult to identify the white blood cell based on this raw on-focus image, and it may also be difficult to distinguish the white blood cell from other entities (e.g., platelets or platelet clusters). As can be observed, the bright entity is less visible in the off-focus image ( FIG. 10B ). Furthermore, it may be difficult to classify the white blood cell into a specific type of white blood cell (e.g., lymphocyte, granulocyte, monocyte, neutrophil, striped neutrophil, eosinophil, basophil, macrophage, and / or blast cell). In some applications, the computer processor performs normalization based on the on-focus and off-focus images (e.g., by subtracting one of the images from the other or by dividing one of the images by the other). Typically, based on the normalization, bright entities become more clearly visible, and the computer processor can identify the bright entities as white blood cells and / or classify white blood cells into particular types of white blood cells with higher confidence than would be possible based on the raw on-focus image alone. (Note that in some applications, the two images are not actually normalized to each other, but rather the computer processor performs processing steps that are equivalent to normalizing the images or portions of the images to each other.)

[0118] 9A-9B and 10A-10B, in some applications, a computer processor identifies one or more entities in a sample (e.g., by distinguishing one or more entities from other entities) based at least in part on an off-focus image of a monolayer of cells in the sample. In some such applications, normalization is performed based on the on-focus and off-focus images, and the computer processor identifies one or more entities in the sample (e.g., by distinguishing one or more entities from other entities) based on the normalization. While the examples shown in FIGS. 9A-9B and 10A-10B relate to platelets and white blood cells, in some applications, generally similar techniques are used to identify other entities, such as abnormal white blood cells, circulating tumor cells, red blood cells, reticulocytes, Howell-Jolly bodies, sickle cells, and teardrop-shaped red blood cells.

[0119] Referring again to Figures 9A-9B and 10A-10B, it can be further observed that the outlines of cells (particularly red blood cells, echinocytes, and other red blood cell types) are more clearly visible in the off-focus images than in the on-focus images. In some applications, the reason these outlines are more clearly visible in the off-focus images is because some refraction and / or diffraction effects are reduced compared to the on-focus images. Figures 11A-12C show some further examples of this.

[0120] 11A-11B, which are example bright-field microscope images of a cell monolayer of a blood sample acquired using green illumination with the microscope focal plane set to coincide with the cell monolayer (FIG. 11A) and with the microscope focal plane set to be off-focus relative to the cell monolayer (FIG. 11B), respectively, in accordance with some applications of the present invention. As can be observed, even in the off-focus image acquired under green illumination, the outlines of cells (particularly red blood cells, echinocytes, and other red blood cell types) are more clearly visible than in the on-focus image.

[0121] 12A to 12C, which are example bright-field microscope images of a cell monolayer of a blood sample acquired using green illumination, according to some applications of the present invention, with the microscope focal plane set to coincide with the cell monolayer (FIG. 12A) and with the microscope focal plane set to be off-focus relative to the cell monolayer (FIGS. 12B and 12C). FIG. 12B was acquired with the microscope focal plane set closer to the microscope objective than the cell monolayer, while FIG. 12C was acquired with the microscope focal plane set farther from the microscope objective than the cell monolayer. As can be seen, in the off-focus images acquired with the microscope focal plane set closer to or farther from the microscope objective than the cell monolayer, the outlines of the cells (particularly red blood cells, echinocytes, and other red blood cell types) are more clearly visible than in the on-focus images.

[0122] 9A-9B, 10A-10B, and 11A-12C, in some applications of the present invention, a computer processor determines contours of one or more entities in the blood sample based on the off-focus image. In some applications, the computer processor determines additional parameters of the one or more entities based on the determined contours. For example, the computer processor may determine a cell volume, a cell area, an average cell volume, and / or an average cell area based on the determined contours.

[0123] In some applications, the computer processor determines one or more parameters of the sample (and / or entities disposed within the sample) using a machine learning classifier, such as a neural network (e.g., a convolutional neural network). In some applications, parameters derived from one or more off-focus images are used as inputs to the machine learning classifier, which in response determines parameters of the sample (and / or entities disposed within the sample). For example, parameters derived from the off-focus images can be used as inputs to a classifier that estimates cellular hemoglobin, cell volume, mean cellular hemoglobin, mean cell volume, and / or additional parameters.

[0124] In most cases, even after allowing a blood sample to settle to form a monolayer using the techniques described herein, not all of the platelets in the blood sample settle within the monolayer, and some cells remain suspended in the cell solution. In some applications, to accurately estimate the number of platelets in a sample, in addition to identifying platelets within the monolayer focus level, platelets suspended in the cell solution are identified. Typically, such platelet identification is achieved by focusing a microscope at additional depth levels relative to one or more depth levels at which the microscope is focused to image the cell monolayer, and acquiring images at these additional depth levels. Typically, platelets are identified and counted in the images acquired at the additional depth levels, and the total number of platelets suspended in the cell solution is estimated based on the number of platelets counted in those images.

[0125] In some applications, in addition to acquiring an on-focus image at each of the additional depth levels, an off-focus image of the additional depth level (i.e., an image offset along the optical axis relative to the focal plane of the additional depth level) is acquired. Typically, the off-focus microscope image is acquired by setting the focal plane of the microscope at a predetermined offset relative to the additional depth level. In some applications, the off-focus microscope image is acquired by setting the focal plane of the microscope at an offset of more than 20 microns and / or less than 100 microns, e.g., 20 to 100 microns, relative to the additional depth level. Alternatively or additionally, the off-focus microscope image is acquired by setting the focal plane of the microscope at an offset of more than 1 times the focal depth of the microscope and / or less than 5 times the focal depth of the microscope, e.g., 1 to 5 focal depths of the microscope, relative to the additional depth level. In some such applications, platelets are identified at the additional depth levels based at least in part on the off-focus image of the additional depth level, e.g., according to the techniques described above.

[0126] According to the above description, when an on-focus image of a given region of a monolayer is compared with an off-focus image of the same region, certain effects are typically expected. In some applications, to verify that an on-focus image of a given region of the monolayer is in optimal focus for the monolayer, an off-focus image of the region is acquired (typically by setting the focal plane of the microscope at a predetermined offset relative to the on-focus image). The off-focus image and the on-focus image are then analyzed, and based at least in part on this analysis, a computer processor determines whether the on-focus image is truly in optimal focus for the monolayer. For example, in response to detecting that cell outlines are not as clearly visible in the on-focus image as in the off-focus image, the computer processor can determine that the on-focus image is not in optimal focus for the monolayer. In response, the computer processor can refocus the microscope before acquiring another on-focus image.

[0127] In some applications, the sample described herein is a sample containing blood or a component thereof (e.g., a diluted or undiluted whole blood sample, a sample containing primarily red blood cells, or a diluted sample containing primarily red blood cells), and parameters related to components of blood, such as platelets, white blood cells, abnormal white blood cells, circulating tumor cells, red blood cells, reticulocytes, Howell-Jolly bodies, sickle cells, teardrop cells, etc., are determined.

[0128] In some applications, the devices and methods described herein are applied, mutatis mutandis, to biological samples other than blood, such as saliva, semen, sweat, sputum, vaginal fluid, feces, breast milk, bronchoalveolar lavage fluid, gastric lavage fluid, tears, and / or nasal secretions. The biological sample can be collected from any living organism, typically a warm-blooded animal. In some applications, the biological sample is from a mammal, e.g., a human. In some applications, the sample is collected from captive animals, zoo animals, and livestock, including, but not limited to, dogs, cats, horses, cows, and sheep. Alternatively or additionally, the biological sample is collected from animals that act as disease vectors, including deer or rats.

[0129] In some applications, the devices and methods described herein are applied to non-bodily samples. In 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, mutatis mutandis. In some embodiments, the sample is a food sample, such as a meat sample, a dairy sample, a water sample, a washings sample, a beverage sample, and / or any combination thereof.

[0130] 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 or in association with any instruction execution system, such as a computer or computer processor 28. For purposes of this description, a computer-usable or computer-readable medium can be any apparatus that can contain, store, communicate, propagate, or transfer a program for use by or in association with an 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. Typically, the computer-usable or computer-readable medium is a non-transitory computer-usable or computer-readable medium.

[0131] Examples of a computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, a random access memory (RAM), a read-only memory (ROM), a rigid magnetic disk, and an optical disk, current examples of which include a compact disk read-only memory (CD-ROM), a compact disk read / write (CD-R / W), and a DVD.

[0132] A data processing system suitable for storing and / or executing program code includes at least one processor (e.g., computer processor 28) coupled directly or indirectly to memory elements (e.g., memory 30) via a system bus. The memory elements may include local memory used during the actual execution of the program code, mass storage devices, and cache memory that provides temporary storage of at least some program code to reduce the number of times the code must be retrieved from mass storage devices during execution. The system is capable of reading instructions of the present invention on a program storage device and performing the method of an embodiment of the present invention in accordance with these instructions.

[0133] Network adapters may be coupled to the processor to enable the processor to be coupled to other processors or remote printers or storage devices over private or public networks. Modems, cable modems, and Ethernet cards are just a few of the currently available types of network adapters.

[0134] Computer program code for carrying out 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++, and conventional procedural programming languages, such as the C programming language or similar programming languages.

[0135] It will be understood that the algorithms described herein may be embodied by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine whereby the instructions, executed by the computer's processor (e.g., computer processor 28) or other programmable data processing apparatus, produce means for performing the functions / acts specified in the algorithms described herein. These computer program instructions may also be stored on a computer-readable medium (e.g., a non-transitory computer-readable medium) to direct the computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored on the computer-readable medium produce an article of manufacture including flowchart blocks and instruction means for performing the functions / acts specified in the algorithms. The computer program instructions may also be loaded into a computer or other programmable data processing apparatus and cause the computer or other programmable device to perform a series of operational steps to produce a computer-implemented process whereby the instructions executing on the computer or other programmable device provide a process for performing the functions / acts specified in the algorithms described herein.

[0136] Computer processor 28 is typically a hardware device that is programmed with computer program instructions to create a dedicated computer. For example, when programmed to execute the algorithms described herein, computer processor 28 typically functions as a dedicated sample analysis computer processor. Typically, the operations described herein performed by computer processor 28 change the physical state of memory 30, which is an actual physical item, to have a different magnetic polarity, charge, etc., depending on the memory technology used.

[0137] The devices and methods described herein may be used in conjunction with the devices and methods described in any one of the following patents or patent applications, all of which are incorporated herein by reference: U.S. Patent No. US9,522,396 to Bachelet U.S. Patent No. US 10,176,565 to Greenfield U.S. Patent No. US 10,640,807 to Pollak U.S. Patent No. US9,329,129 to Pollak U.S. Patent No. US 10,093,957 to Pollak US Patent No. US10,831,013 to Yorav Raphael U.S. Patent No. US 10,843,190 to Bachelet US Patent No. US10,482,595 to Yorav Raphael U.S. Patent No. US 10,488,644 to Eshel International Publication No. WO17 / 168411 to Eshel U.S. Patent Application Publication No. US2019 / 0302099 to Pollak U.S. Patent Application Publication No. US2019 / 0145963 to Zait International Publication No. WO19 / 097387 to Yorav-Raphael

[0138] It will be appreciated by those skilled in the art that the present invention is not limited to what has been specifically shown and described above. The scope of the present invention includes both combinations and subcombinations of the various features described above, as well as variations and modifications thereof that would occur to one skilled in the art upon reading the foregoing description, and that are not present in the prior art.

Claims

1. 1. A method for use with a blood sample containing cells, comprising: allowing some cells in the blood sample to settle to form a monolayer at a focal level; focusing the microscope so that the monolayer focus level and the focal plane of the microscope are at least approximately coincident; acquiring at least one on-focus microscope image of the blood sample with the focal plane of the microscope substantially coincident with the monolayer focus level; focusing the microscope so that the focal plane of the microscope is offset relative to the single focus level; acquiring at least one off-focus microscope image of the blood sample with the focal plane of the microscope offset relative to the monolayer focus level; identifying one or more entities within the blood sample based at least in part on the on-focus and off-focus images; the one or more entities are selected from the group consisting of platelets, leukocytes, lymphocytes, granulocytes, monocytes, neutrophils, striped neutrophils, eosinophils, basophils, macrophages, and blast cells; method.

2. 2. The method of claim 1, wherein acquiring at least one off-focus microscopic image of the blood sample with the focal plane of the microscope offset relative to the monolayer focus level comprises acquiring at least one off-focus microscopic image of the blood sample with the focal plane of the microscope offset relative to the monolayer focus level by an offset of more than 20 microns and less than 100 microns or an offset of more than 1x and less than 5x depth of focus of the microscope.

3. 2. The method of claim 1, wherein determining a characteristic of at least a portion of the blood sample based at least in part on the on-focus and off-focus images comprises inputting the on-focus and off-focus images to a machine learning classifier, the machine learning classifier being configured to determine a characteristic of the at least a portion of the blood sample based at least in part on the on-focus and off-focus images.

4. 2. The method of claim 1, wherein determining a characteristic of at least a portion of the blood sample based at least in part on the on-focus and off-focus images comprises deriving one or more parameters from the on-focus and off-focus images and inputting the one or more derived parameters into a machine learning classifier, the machine learning classifier being configured to determine a characteristic of the at least a portion of the blood sample based at least in part on the derived parameters.

5. The method of claim 1, wherein acquiring at least one off-focus microscopic image of the blood sample while the focal plane of the microscope is offset relative to the monolayer focus level comprises acquiring at least one off-focus microscopic image of the blood sample while illuminating the sample with light having a wavelength between 505 nm and 535 nm.

6. The method of claim 1, wherein acquiring at least one off-focus microscopic image of the blood sample with the focal plane of the microscope offset relative to the monolayer focus level comprises acquiring at least one off-focus microscopic image of the blood sample while illuminating the blood sample with light having a wavelength between 400 nm and 450 nm.

7. The method of claim 1, wherein acquiring at least one off-focus microscopic image of the sample with the focal plane of the microscope offset relative to the monolayer focus level comprises acquiring at least one off-focus microscopic image of the blood sample while illuminating the sample with light having a wavelength between 620 nm and 640 nm.

8. 2. The method of claim 1, wherein focusing the microscope so that the focal plane of the microscope is offset relative to the single-layer focal level comprises focusing the microscope so that the focal plane of the microscope is set closer to an objective lens of the microscope than the single-layer focal level.

9. 2. The method of claim 1, wherein focusing the microscope so that the focal plane of the microscope is offset relative to the single focus level comprises focusing the microscope so that the focal plane of the microscope is set farther from the microscope objective lens than the single focus level.

10. 2. The method of claim 1, wherein focusing the microscope so that the focal plane of the microscope is offset relative to the monolayer focal level comprises focusing the microscope so that the focal plane of the microscope is offset by 20 microns to 100 microns relative to the monolayer focal level.

11. 2. The method of claim 1, wherein focusing the microscope so that the focal plane of the microscope is offset relative to the single layer focal level comprises focusing the microscope so that the focal plane of the microscope is offset relative to the single layer focal level by 1 to 5 focal depths of the microscope.

12. 2. The method of claim 1, wherein identifying one or more entities within the blood sample based at least in part on the on-focus and off-focus images comprises: normalizing the on-focus and off-focus images relative to one another; and identifying one or more entities within the blood sample based at least in part on the normalization.

13. 1. A device for use with a blood sample containing cells, comprising: A microscope and 1. A computer processor comprising: focusing the microscope so that the focal plane of the microscope is at least approximately coincident with a monolayer focus level at which at least some cells that are part of the blood sample have settled to form a monolayer; operating the microscope to acquire at least one on-focus microscope image of the blood sample with the focal plane of the microscope substantially coincident with the monolayer focus level; focusing the microscope so that the focal plane of the microscope is offset relative to the single layer focus level; driving the microscope to acquire at least one off-focus microscopic image of the blood sample with the focal plane of the microscope offset relative to the monolayer focus level; a computer processor configured to identify one or more entities within the blood sample based at least in part on the on-focus and off-focus images; Equipped with the one or more entities are selected from the group consisting of platelets, leukocytes, lymphocytes, granulocytes, monocytes, neutrophils, striped neutrophils, eosinophils, basophils, macrophages, and blast cells; Device.

Images