Abstract: Apparatus and methods are described for analyzing a bodily sample. A microscope system acquires one or more microscope images of the bodily sample. A computer processor identifies elements as being candidates of a given entity, in the one or more images. At least one sample-informative feature, relating to a characteristic of the candidates of the given entity in the sample as a whole, is extracted from the one or more images. A characteristic of the sample is determined at least partially based upon the sample-informative feature, and an output is generated in response thereto. Other applications are also described.

Abstract: Apparatus and methods are described for analyzing a bodily sample. One or more microscope images of the bodily sample are acquired. Using at least one computer processor at least one sample-informative feature that is indicative of a characteristic of the bodily sample is extracted from the images. Based upon the sample-informative feature, the computer processor determines that there is a defect associated with the bodily sample, and determines a source of the defect. Other applications are also described.

Abstract: Apparatus and methods are described including analyzing one or more microscopic images of the blood sample using a machine-learning classifier. An entity within the one or more microscopic images is identified using a first classification model, and a first estimated concentration of the entity within the sample is determined, based upon the entity as identified using the first classification model. The entity is identified within the one or more microscopic images using a second classification model, and a second estimated concentration of the entity within the sample is determined, based upon the entity as identified using the second classification model. The first and second estimated concentrations are compared to each other, and, in response to the comparison, a hybrid classification model that is a hybrid of the first and second classification models is used. Other applications are also described.

Abstract: Apparatus and methods are described for use with a blood sample. Using a microscope (24), three images of a microscopic imaging field of the blood sample are acquired, each of the images being acquired using respective, different imaging conditions, and the first one of the three images being acquired under violet-light brightfield imaging. Using at least one computer processor (28), an artificial color microscopic image of the microscopic imaging field is generated, by mapping the first one of the three images to a red channel of the artificial color microscopic image, mapping a second one of the three images to a second color channel of the artificial color microscopic image, and mapping a third one of the three images to a third color channel of the artificial color microscopic image. Other applications are also described.

Abstract: Apparatus and methods are described use with a bodily sample that contains cells. A microscope (24) is focused, such that a focal plane of the microscope (24) at least approximately coincides with a level at which at least some cells belonging to the sample are at least partially disposed. At least one on-focus microscopic image of the sample, while the focal plane of the microscope (24) approximately coincides with the level. The microscope (24) is focused such that the focal plane of the microscope is offset with respect to the level, at least one off-focus microscopic image of the sample is acquired, while the focal plane of the microscope (24) is offset with respect to the level. A property of at least a portion of the sample is determined, at least partially based upon the on-focus and off-focus images. Other applications are also described.

Abstract: Apparatus and methods are provided including imaging a blood sample that is a cell suspension deposited in a sample chamber. The cells are allowed to settle in the sample chamber to form a monolayer of cells. At least one microscopic image is acquired of the monolayer of cells using a microscope (24) while the microscope is focused at a monolayer-depth-level, and a first platelet count of platelets that have settled within the monolayer, is determined. An additional microscopic image of the simple is acquired, while the microscope is focused at a different depth level from the monolayer-depth-level, and a second platelet count of platelets that have not settled within the monolayer is determined. An output is generated based upon the first and second platelet counts. Other applications are also described.

Abstract: Apparatus and methods are described including preparing a blood sample for analysis by depositing the blood sample within a sample chamber (52), and placing the sample chamber, with the blood sample deposited therein, within a microscopy unit (24). One or more microscopic images of the sample chamber (52) with the blood sample deposited therein are acquired, using a microscope of the microscopy unit. Based upon the one or more images, an amount of one or more cell types within the sample chamber that had already settled within the sample chamber, prior to acquisition of the one or more microscopic images is determined. A characteristic of the sample is determined, at least partially in response thereto. Other applications are also described.

Abstract: Apparatus and methods are described including placing at least a portion of a blood sample within a sample chamber (52), and acquiring microscopic images of the portion of the blood sample. Candidates of a given entity within the blood sample are identified, within the microscopic image. At least some of the candidates as being the given entity are validated, by performing further analysis of the candidates. A count of the candidates of the given entity is compared to a count of the validated candidates of the given entity, and at least the portion of the sample is invalidated from being used for performing at least some measurements upon the sample, at least partially based upon a relationship between the count of candidates and the count of validated candidates. Other applications are also described.

Abstract: Apparatus and methods are described for analyzing a bodily sample. A microscope system acquires one or more microscope images of the bodily sample. A computer processor identifies elements as being candidates of a given entity, in the one or more images. At least one sample-informative feature, relating to a characteristic of the candidates of the given entity in the sample as a whole, is extracted from the one or more images. A characteristic of the sample is determined at least partially based upon the sample-informative feature, and an output is generated in response thereto. Other applications are also described.

Abstract: Apparatus and methods are described including staining a blood sample with one or more stains. A plurality of microscopic images of the stained blood sample are acquired, using a microscope. Staining-quality parameters for respective microscopic images are determined, using a computer processor, the staining-quality parameters being indicative of a quality of the staining within each of the respective microscopic images. An action is performed by the computer processor, based upon the staining-quality parameters of the respective microscopic images. Other applications are also described.

Abstract: Apparatus and methods are described for analyzing a bodily sample. One or more microscope images of the bodily sample are acquired. Using at least one computer processor at least one sample-informative feature that is indicative of a characteristic of the bodily sample is extracted from the images. Based upon the sample-informative feature, the computer processor determines that there is a defect associated with the bodily sample, and determines a source of the defect. Other applications are also described.

Abstract: Apparatus and methods are described including acquiring microscopic images of a blood sample, and identifying deformed red blood cells within the microscopic images. A degree of red blood cell deformity within the sample is determined, at least partially based upon the identified deformed red blood cells. A sample-informative parameter that is indicative of a characteristic of the blood sample as a whole is determined, at least partially based upon the degree of red blood cell deformity within the sample. Other applications are also described.

Abstract: Apparatus and methods are described including measuring hematocrit within a blood sample, by performing a first measurement on a first portion of the blood sample. Mean corpuscular volume in the blood sample is measured, by performing a second measurement on a second portion of the blood sample, the second portion being diluted with respect to the first portion. A red blood cell count per unit volume within the blood sample is determined by dividing the hematocrit measured within the first portion by the mean corpuscular volume measured within the second portion. Other applications are also described.

Abstract: Apparatus and methods are described for use with a blood sample (48, 50), including measuring hemoglobin concentration within at least a portion (48) of the blood sample, by performing a first measurement on the blood sample. Mean corpuscular hemoglobin in the blood sample (48, 50) is measured, by performing a second measurement on the blood sample (48, 50). A parameter of the blood sample is determined, based on a relationship between the concentration of hemoglobin and the mean corpuscular hemoglobin. Other applications are also described.

Abstract: Apparatus and methods are described including placing a first portion of a biological sample into a source sample portion chamber of a sample carrier, and placing a second portion of the biological sample into a diluted sample portion chamber. The second portion of the biological sample is diluted with respect to the first portion of the biological sample. Using an optical measurement device, a bulk-level measurand of the sample that relates to a parameter of the biological sample as a whole is measured, by performing a measurement upon the first portion of the biological sample. Microscopic images of the second portion of the biological sample are acquired. Other applications are also described.

Abstract: Apparatus and methods are described including acquiring microscopic images of a blood sample, and identifying deformed red blood cells within the microscopic images. A degree of red blood cell deformity within the sample is determined, at least partially based upon the identified deformed red blood cells. A sample-informative parameter that is indicative of a characteristic of the blood sample as a whole is determined, at least partially based upon the degree of red blood cell deformity within the sample. Other applications are also described.

Abstract: Apparatus and methods are described including staining a blood sample with one or more stains. A plurality of microscopic images of the stained blood sample are acquired, using a microscope. Staining-quality parameters for respective microscopic images are determined, using a computer processor, the staining-quality parameters being indicative of a quality of the staining within each of the respective microscopic images. An action is performed by the computer processor, based upon the staining-quality parameters of the respective microscopic images. Other applications are also described.

Abstract: Apparatus and methods for analyzing a bodily sample are described. A microscope system acquires one or more microscope images of the bodily sample. A computer processor identifies, in the one or more images, at least one element as being a candidate of a given entity. The computer processor extracts, from the one or more images, at least one candidate-informative feature associated with the candidate of the given entity, and at least one sample-informative feature that is indicative of a characteristic of the bodily sample as a whole. The computer processor processes the candidate-informative feature in combination with the sample-informative feature, and generates an output upon the output device, in response thereto. Other applications are also described.

Abstract: Apparatus and methods for analyzing a bodily sample are described. A microscope system acquires one or more microscope images of the bodily sample. A computer processor identifies, in the one or more images, at least one element as being a candidate of a given entity. The computer processor extracts, from the one or more images, at least one candidate-informative feature associated with the candidate of the given entity, and at least one sample-informative feature that is indicative of a characteristic of the bodily sample as a whole. The computer processor processes the candidate-informative feature in combination with the sample-informative feature, and generates an output upon the output device, in response thereto. Other applications are also described.

Abstract: Apparatus and methods are described including a microscope system (11) configured to acquire one or more microscope images of a bodily sample, an output device (34), and at least one computer processor (28). The computer processor identifies, in the one or more images, at least one element as being a pathogen candidate, and extracts, from the one or more images, at least one candidate-informative feature associated with the pathogen candidate. The compute processor extracts, from the one or more images, at least one sample-informative feature that is indicative of contextual information related to the bodily sample. The computer processor classifies a likelihood of the bodily sample being infected with a pathogenic infection, by processing the candidate-informative feature in combination with the sample-informative feature, and generates an output upon the output device, in response thereto. Other applications are also described.