Abstract: A method is proposed for segmenting a brain image into a CSF region, a WM region and a GM region. An upper limit for the intensity values of a CSF region in the image is estimated such that the points of the image having an intensity less than this upper limit include a subset of the points which form a spatially connected group and which have a peaked intensity distribution. In other words, the invention exploits both the expected spatial distribution and expected intensity distribution of the CSF region. This makes it possible for the method to provide reliable discrimination of the CSF region even in CT images with poor image quality. Various methods are proposed for using the upper limit, and for improving the segmentation accuracy.

Abstract: Colonies growing on a culture medium surface may be more accurately counted with reduced variation in the counts obtained by capturing a plurality of images of the entire culture medium surface, wherein successive images are captured following rotation of the culture medium surface relative to the image capture apparatus by n/360 degrees where n is the number of images to be captured; performing data processing on image data of the entire culture medium surface of the petri dish at each specified angle; and the number of colonies in the petri dish is calculated by performing numerical processing on the number of colonies counted separately at each specified angle.

Abstract: Apparatuses, methods, and systems for automated, non-invasive evaluation of cell activity are provided. In one embodiment, an apparatus includes a hypothesis selection module configured to select a hypothesis from a plurality of hypotheses characterizing one or more cells shown in an image. Each of the plurality of hypotheses includes an inferred characteristic of the one or more cells based on geometric features of the one or more cells shown in the image. The hypothesis selection module is implemented in at least one of a memory or a processing device.

Abstract: The invention provides a method and apparatus for isolating individual target cells. The apparatus includes a body structure comprising a main channel, a collection channel, and a waste channel fluidly coupled at a first fluid junction. A plurality of trapping channels intersect the collection channel, each trapping channel having a diameter at a location adjacent to the intersection of the trapping channel with the collection channel that is less than a diameter of an individual target cell. The apparatus also includes an imaging system configured to image individual target and non-target cells within the main channel, thereby producing imaging data; a processor configured to perform real-time, multivariate analyses of the imaging data; and a directing system configured to direct the individual target cells. A pressure source is in fluid communication with one or more of the collection channel, the waste channel, the first side channel, and the second side channel.

Abstract: At least first and second digital images of the sample are acquired having different focal heights relative to a platform on which the cells are disposed. A contrast matrix is produced having elements computed in dependence upon the difference between the values of the corresponding pixels in the first and second images. A phase matrix is produced by convolution of the contrast matrix with a predetermined distance matrix. The phase matrix is used to assess characteristics of the sample, such as the presence of cells in the sample or the heights of cells in the sample.

Abstract: Apparatuses, methods, and systems for automated cell classification, embryo ranking, and/or embryo categorization are provided. An apparatus includes a classification module configured to apply classifiers to images of one or more cells to determine, for each image, a classification probability associated with each classifier. Each classifier is associated with a distinct first number of cells, and is configured to determine the classification probability for each image based on cell features including one or more machine learned cell features. The classification probability indicates an estimated likelihood that the distinct first number of cells is shown in each image. The classification module is further configured to classify each image as showing a second number of cells based on the distinct first number of cells and the classification probabilities associated therewith. The classification module is implemented in at least one of a memory or a processing device.

Abstract: The invention relates generally to a process of analyzing and visualizing the expression of biomarkers in an individual cell wherein the cell is examined to develop patterns of expression by using a grouping algorithm, and a system to perform and display the analysis.

Abstract: A cell-image analyzing apparatus is intended to analyze, using a cell image, a cell collective that forms a colony, and is provided with a computer. The cell-image analyzing apparatus has an image analysis software that makes the computer function as: a boundary element extracting means for extracting boundary elements of subjects upon analyzing the cell image; a possible colony region determining means for determining, as a possible colony region, a region surrounded by boundary elements of subjects and having a size greater than a first criterion value; and a colony region determining means for determining, in the possible colony region, a region containing more than a predetermined number of clustered regions each being surrounded by boundary elements of subjects and having a size smaller than a second criterion value, as a colony region.

Abstract: Provided are methods for determining and analyzing photometric and morphometric features of small objects, such as cells to, for example, identify different cell states. In particularly, methods are provided for identifying apoptotic cells, and for distinguishing between cells undergoing apoptosis versus necrosis.

Abstract: From a sample image, a fertilization test method determines the ratio of fertilized cells in the image by identifying cells in the image and calculating cell properties for each cell. An area is determined between a cell body and an outer search limit to search for a fertilization membrane. A cell outline is defined for each cell and cell membrane edges are found within the search area by changing the cell outline size between the cell body boundary the outer search limit, checking for a match with detected cell membrane edges. A cell is determined to be fertilized based on matches between detected cell membrane edges and the cell outline, patterns of contrast changes indicated by a cell membrane, or circles fit to cell membrane edges.

Abstract: A method of predicting hepatotoxicity of a compound. The method includes imaging cells of hepatic origin positioned within a plurality of containers to obtain imaged cellular targets, each container being treated with a different concentration of the compound, the imaging being performed using a quantitative high-content cell imaging system; quantitatively measuring the imaged cellular targets to detect changes in multiple cellular targets associated with cytotoxicity of the compound; and analyzing measurements obtained from the measured imaged cellular targets over a range of compound concentrations to determine the hepatotoxicity of the compound.

Abstract: A method is provided for scaling an image taken at a given exposure time to a selected exposure time. The method generally comprises: determining a dark pixel intensity of an imaging device; acquiring a first image at a given exposure time; and adjusting a pixel intensity of one or more pixels in the first image, based at least in part on the dark pixel intensity, for a second exposure time that is different from the given exposure time.

Abstract: The invention provides systems and methods for detection, grading, scoring and tele-screening of cancerous lesions. A complete scheme for automated quantitative analysis and assessment of human and animal tissue images of several types of cancers is presented. Various aspects of the invention are directed to the detection, grading, prediction and staging of prostate cancer on serial sections/slides of prostate core images, or biopsy images. Accordingly, the invention includes a variety of sub-systems, which could be used separately or in conjunction to automatically grade cancerous regions. Each system utilizes a different approach with a different feature set. For instance, in the quantitative analysis, textural-based and morphology-based features may be extracted at image- and (or) object-levels from regions of interest.

Abstract: Systems and methods for assessing and optimizing virtual microscope slide image quality are provided. In order to determine whether any of multiple virtual slide images has an out of focus area and is therefore a candidate for manual inspection or rescanning, various focus points used to scan each virtual slide image are used to calculate a best fit surface for each virtual slide image. The best fit surface is then used to determine whether any of the various focus points are outliers. If it is determined that a virtual slide image is associated with outlying focus points, it is identified as a candidate for manual inspection or rescanning.

Abstract: A method for analysing microbial growth on a solid culture medium, the method including obtaining image data of the solid culture medium and any microbial growth, generating an associated feature vector of values obtained by applying one or more filters to the image data, using a classifier to classify each pixel in a plurality of pixels in the image data based on the associated feature vector, analysing results of pixel classifications of each said pixel to derive a microbiological assessment of the solid culture medium and any microbial growth, and outputting the microbiological assessment.

Abstract: A system and method for displaying images of internal anatomy includes an image processing device configured to provide high resolution images of the surgical field from low resolution scans during the procedure. The image processing device digitally manipulates a previously-obtained high resolution baseline image to produce many representative images based on permutations of movement of the baseline image. During the procedure a representative image is selected having an acceptable degree of correlation to the new low resolution image. The selected representative image and the new image are merged to provide a higher resolution image of the surgical field. The image processing device is also configured to provide interactive movement of the displayed image based on movement of the imaging device, and to permit placement of annotations on the displayed image to facilitate communication between the radiology technician and the surgeon.

Abstract: Simple, high-precision cell tracking is realized. Provided is a method for tracking cells, comprising an image acquisition step (S1) of acquiring a plurality of observation images including a plurality of cells in the field of view at certain time intervals; a feature analysis step (S2) of analyzing predetermined brightnesses of the individual cells in the observation images acquired in the image acquisition step (S1); a grouping step (S3) of grouping the cells for each of the observation images on the basis of the brightnesses analyzed in the feature analysis step (S2) and a predetermined threshold value for classifying the brightnesses; and an associating step (S4) of associating, for each of the groups divided in the grouping step (S3), the cells whose morphological features are substantially the same between the observation images acquired at different times.

Abstract: A three-dimensional model is determined from a two-dimensional sketch. Rather than or in addition to modification of 3D constraints to reduce gaps in the 3D model, 2D constraints are modified. The geometry of the 2D sketch is altered in the view plane (x, y) or 2D input instead of maintaining the geometry of the 2D sketch and only modifying in the view direction (z). Gaps may be reduced through alteration of the 2D geometry.

Abstract: The invention relates to a computer implemented method and systems for cell level fish dot counting. FISH (fluorescence in situ hybridization) dot counting is the process of enumerating chromosomal abnormalities in the cells which can be used in areas of diagnosis and cancer research. The method comprises in part overlaying images of a biological sample comprising a nuclear counterstain mask and a FISH binary mask. The FISH binary mask is extracted using a multi-level extended h-maxima or h-minima.

Abstract: A new family of morphological features, referred to herein as threshold compactness features, is provided, useful for automated classification of objects, such as cells, in images. In one embodiment, one or more thresholds and/or binary masks are applied to an image, and one or more provisional objects within a cell in the image are automatically identified. The threshold compactness of the cell is computed as a function of area S of the one or more provisional objects and border length P of the one or more provisional objects. Computation of threshold compactness allows cells in an image to be distinguished and characterized. Compared to previous techniques, the methods and apparatus described herein are more robust and computationally efficient.

Abstract: Embodiments of the present disclosure provides improved methods for determining the presence of abnormalities in exfoliated cells. In one embodiment, the present disclosure provides methods for reconstructing cellular spectrum of a cell sample by creating a spectral map of the cellular sample, generating a binary mask of the spectral map, removing edge artifacts from each cell, and co-adding spectral data of each pixel corresponding to the cell to reconstruct the spectrum of each cell.

Abstract: Platelets or blood cells are detected in a fluid sample by adjusting a focal depth of a microscope through a range of values, the microscope having a mounted sample and an objective lens adapted with one or both of (a) a spherical aberration correction unmatched to a utilized cover plate for the sample, or (2) a numerical aperture unmatched to a utilized illumination source for the sample. Images are recorded at different specific focal depths and in multiple z planes of a fluid bearing the platelets, where the position of platelets may overlap on different of the multiple z planes that are recorded, the images recorded through the cover plate, thus causing the generation of a specific light-dark pattern indicative of platelets at particular positions and at multiple depths in the fluid media. The images are analyzed for the specific light-dark pattern.

Abstract: Disclosed herein are methods and devices for sectioning cell colonies. Also disclosed are methods of purifying cell colonies. A method of sectioning cell colonies can include providing a cell colony on a culture plate comprising a known thickness; positioning a bottom of the culture plate using automated focus technology; and sectioning the cell colony into one or more pieces using a pattern of laser cutting lines. Devices for performing the method are also disclosed.

Abstract: Feature analysis on consecutive tissue sections (FACTS) includes obtaining a plurality of consecutive tissue sections from a tissue sample, staining the sections with at least one biomarker, obtaining a digital image thereof, and identifying one or more regions of interest within a middle of the consecutive tissue sections. The digital images of the consecutive tissue sections are registered for alignment and the one or more regions of interest are transferred from the image of the middle section to the images of the adjacent sections. Each image of the consecutive tissue sections is then analyzed and scored as appropriate. Using FACTS methods, pathologist time for annotation is reduced to a single slide. Optionally, multiple middle sections may be annotated for regions of interest and transferred accordingly.

Abstract: A pathological diagnosis support apparatus into which a digital color image showing a stained tissue sample is input, the apparatus including: a display that performs a display operation; and an image processor that when the digital color image is input, extracts cell nucleus areas, cytoplasm areas and glandular cavity areas, respectively, based on luminance values of pixels of the digital color image, measures basic feature quantities representing features of shapes of the respective cell nucleus areas, cytoplasm areas and glandular cavity areas, which have been extracted, determines whether or not a particular kind of area that appears in a limited case according to the disease state of the tissue sample exists, for each of the cell nucleus areas, the cytoplasm areas and the glandular cavity areas based on the luminance values and the basic feature quantities, and measures structure feature quantities representing ways in which the cell nucleus areas are positioned, based on the basic feature quantities of

Abstract: Switching between highlighting and unhighlighting of an object determined as adopted and switching between highlighting and unhighlighting of an object determined as not adopted are performed individually and independently by manipulation of an on/off selectable button. This allows switching to be freely performed between the following states in which: objects are highlighted regardless of whether the objects are adopted or not; only an object determined as adopted is highlighted; only an object determined as not adopted is highlighted; and objects are not highlighted regardless of whether the objects are adopted or not. A user visually judges whether the result of the adoption/non-adoption process is proper or not easily while switching between these displays.

Abstract: The present invention relates to methods and devices for analyzing x-ray images. In particular, devices, methods and algorithms are provided that allow for the accurate and reliable evaluation of bone structure and macro-anatomical parameters from x-ray images.

Abstract: A system and method for using pre-procedural images for registration for image-guided therapy (IGT), also referred to as image-guided intervention (IGI), in percutaneous surgical application. Pseudo-features and patient abdomen and organ surfaces are used for registration and to establish the relationship needed for guidance. Three-dimensional visualizations of the vasculature, tumor(s), and organs may be generated for enhanced guidance information. The invention facilitates extensive pre-procedural planning, thereby significantly reducing procedural times. It also minimizes the patient exposure to radiation.

Abstract: There is provided a microparticle sorting device that automatically optimizes a fluid stream. There is provided a microparticle sorting device that includes a voltage supply unit that supplies a driving voltage to a vibratory element that applies vibration to an orifice that produces a fluid stream, a charge unit that imparts charge to at least some droplets ejected from the orifice, deflecting plates, arranged opposing each other with the fluid stream S therebetween, that vary a travel direction of the droplets, and a first image sensor that acquires an image of the droplets passing between the deflecting plates.

Abstract: The subject invention concerns methods for the detection, diagnosis, and/or prognosis of cancer by analyzing centrosomal features. In one embodiment, a method includes receiving an image of one or more cells; selecting a region of interest in one cell; segmenting the region of interest to delineate at least one centrosomal; extracting one or more features from the segmented image; and analyzing the extracted features to diagnose cancer. In another embodiment, the progression of cancer can be predicted through analysis and classification of the extracted features. In one embodiment, the method can be performed by a quantitative cancer analysis system including a diagnosis module and/or a prognosis module. In one embodiment, the method can be performed using an image processing system.

Abstract: The methods and systems disclosed herein include obtaining a first plurality of images of a sample, where each image in the first plurality of images corresponds to a different spectral band of illumination light incident on the sample or emission light from the sample, obtaining a second plurality of images of the sample, where each image in the second plurality of images corresponds to a different spectral band of illumination light incident on the sample or emission light from the sample, aligning the first and second pluralities of images based on information from a first image from the first plurality of images and a second image from the second plurality of images, where the first and second images correspond to a shared spectral band, and combining at least some members of the first plurality of images and at least some members of the second plurality of images to form an image stack.

Abstract: The present invention provides a method for classifying biological tissues with high precision compared to a conventional method. When measuring a spectrum which has a two-dimensional distribution that is correlated with a slice of a biological tissue, and acquiring a biological tissue image from the two-dimensional measured spectrum, the method includes dividing an image region into a plurality of small blocks, and then reconstructing the biological tissue image by using the measured spectrum and a classifier corresponding to each of the regions.

Abstract: A method for concentrating and isolating nucleated cells, such as a maternal and fetal nucleated red blood cells (NRBC's), in a maternal whole blood sample. The invention also provides methods and apparatus for preparing to analyze and analyzing the sample for identification of fetal genetic material as part of prenatal genetic testing. The invention also pertains to methods and apparatus for discriminating fetal nucleated red blood cells from maternal nucleated red blood cells obtained from a blood sample taken from a pregnant woman.

Abstract: There is provided an image processing apparatus that analyzes a pathology image obtained by imaging an analysis object including a setting device for calculating an amount of a luminance difference characteristic as an amount of characteristic of each pixel of a pathology image, and for setting a cellular tissue region in the pathology image, based on the amount of the luminance difference characteristic, using a cellular tissue detector that has studied in advance. The cellular tissue detector may have studied in advance by statistical learning that uses an image corresponding to a cellular tissue.

Abstract: Provided is an image processing apparatus to easily identify an image acquiring position of an image by an adaptive optics SLO. The image processing apparatus analyzes an image of an eye to be inspected shot by an adaptive optics SLO, and includes a frequency conversion portion to frequency-convert the image to acquire a frequency spatial image; a characteristic extracting portion to extract a characteristic amount from the frequency spatial image, the characteristic amount relating to a ring-structure reflecting arrangement of photoreceptor cells; and a position estimating portion to estimate an image acquiring position of the image based on the characteristic amount.

Abstract: A data set of cell profile data is stored. The cell profile data includes multiplexed biometric image data describing the expression of a plurality of biomarkers. Cell profile data is generated from tissue samples drawn from a cohort of patients having an assessment related to the commonality. Multiple sets of clusters of similar cells are generated from the data set; the proportion of cells in each cluster is examined for an association with a diagnosis, a prognosis, or a response; and a predictive set of clusters is selected based on model performance. One predictive set of clusters is selected based on a comparison of the performance of at least one model of the plurality of sets of clusters. Display techniques that aid in understanding the characteristics of a cluster are disclosed.

Abstract: A biological growth plate scanner includes a multi-color illumination system that illuminates a biological growth plate with different illumination colors. A monochromatic image capture device captures images of the biological growth plate during illumination of the growth plate with each of the illumination colors. A processor combines the images to form a composite multi-color image, and/or individual components of the composite image, and analyzes the composite image to produce an analytical result such as a colony count or a presence/absence result. The biological growth plate scanner may include both front and back illumination components. The back illumination component may include a diffuser element disposed under the biological growth plate. The diffuser element receives light from one or more laterally disposed illumination sources, and distributes the light to illuminate a back side of the biological growth plate.

Abstract: Systems and methods for performing cytometry using a linear light sensor. An illumination field, a line scanned by the linear light sensor, or both are swept across a cell to be imaged. Relative motion between the cell and the swept illumination may be created using a movable optical component or components, by adhering cells to a plate and transporting the plate or by other techniques.

Abstract: In one aspect, a method of detecting at least on feature associated with a blood vessel in at least one image of at least one blood vessel using a matched filter adapted to respond to the at least one feature is provided. The method comprises applying a scale detection filter to selected voxels in the at least one image to determine a scale for the matched filter at each of the selected voxels, determining an orientation for the matched filter at each of the selected voxels, wherein determining the orientation is assisted by using the scale determined at each of the selected voxels, applying the matched filter at each of the selected voxels at the scale and the orientation determined at each of the selected voxels to obtain a filter response at each of the selected voxels, and analyzing the filter response at each of the selected voxels to determine if the respective voxel corresponds to the at least one feature.

Abstract: An improved histopathological score is obtained by generating image objects from images of tissue containing stained epithelial cells. First objects are generated that correspond to basal cells stained with a first stain, such as p63. Second objects are generated that correspond to luminal cells stained with a second stain, such as CK18. If the same tissue is not stained with both stains, then the images of differently stained tissue are co-registered. Third objects are defined to include only those second objects that have more than a minimum separation from any first object. A scoring region includes the third objects, and the histopathological score is determined based on tissue that falls within the scoring region. For example, a Gleason score of prostate tissue is determined by classifying tissue patterns in the scoring region. Alternatively, a Gleason pattern is assigned by counting the number of third objects that possess a predetermined form.

Abstract: The present invention provides for an intelligent autofocus method and device for a digital pathology image, method are device are able to couple a feedback from the behaviour of the user, for example by gaze tracking arrangement, to the actually focal representation of an image and adjust the imaging setup accordingly with regard to the focal plane. The adjustment is performed in such a way that the focal plane is selected which optimizes and sharpens the actual object of interest which was previously determined.

Abstract: A method of processing data for comparing at least two images using data processing elements, includes extracting a first sample of coordinate values (X1, . . . , Xn1) from at least one first image (Im1) and a second sample of coordinate values (Y1, . . . , Yn2) from at least one second image (Im2). A normal score value (Z) is then computed, with the processing elements, based on a density test statistic function ({circumflex over (T)}) applied on the first and second samples of coordinate values, wherein this density test statistic function has an asymptotic distribution, and a p-value, derived from the computed normal score value (Z), is compared (400) with a predetermined level of significance (?) in order to determine a similarity between the two images. The method can be used for determining the influence and assessing the cytotoxicity of a compound, monitoring a drug treatment, determining cellular morphology changes and the influence of an infection by pathogens.

Abstract: A first aspect of the invention relates to an apparatus 100 for genotoxicological screening. The apparatus 100 comprises a processor 114 for analyzing images. The processor 114 is configured to provide an identifier module 115 for identifying target cells in an image and a dynamically modifiable classifier module 116 for classifying the identified cells in accordance with one or more phenotype, such as micronuclei, for example. The processor 114 is also configured to provide a scoring module 117 for assigning respective confidence measurements to the classified cells. Various aspects and embodiments of the invention may be used, for example, to provide for improved reliability and accuracy when performing automated high-throughput screening (HTS) drug assays.

Abstract: An image processing apparatus displays an object adopted and an object not adopted by an adoption/non-adoption process in a distinguishable manner. A user designates an object whose adoption/non-adoption result is desired to be reversed among the objects displayed by the image processing apparatus. The image processing apparatus changes an allowable range stored in a storage part so that the adoption/non-adoption result of the designated object is reversed. That is, the user views the adoption/non-adoption result of the objects to change the allowable range of a parameter so that the adoption/non-adoption result becomes proper. This makes the allowable range of the parameter for use in the adoption/non-adoption process proper with ease.

Abstract: A computer-implemented method of processing image data representing biological units in a tissue sample includes receiving a first image of the tissue sample containing signals from an immunofluorescent (IF) morphological marker, wherein the tissue sample is stained with the IF morphological marker, and receiving a second image of the same tissue sample containing signals from a fluorescent probe, wherein the tissue sample is hybridized in situ with the fluorescent probe. The method further includes classifying each biological unit in the tissue sample into one of at least two classes based on a mean intensity of the signals from the IF morphological marker in the first image, performing a fluorescence in situ hybridization (FISH) analysis of the tissue sample in the second image to obtain results therefrom, and filtering the results of the FISH analysis to produce a subset of the results pertaining to biological units classified in one class.

Abstract: The invention relates to a method that includes the following steps: carrying out a treatment of a sample, the treatment being carried out for differentiating diseased cells from healthy cells in the sample (4); carrying out at least one first image acquisition of the sample (4) provided on an analysis plate (8) so as to obtain a plurality of images, each representing an area (18) of the analysis plate, said images being arranged side by side so as to form an image of the entirety of the sample in order to create a virtual analysis plate (2), locating a reference plane of the analysis plate including a slide and a lamella provided above the slide for image acquisition, said reference plane being defined by the surface of the slide or the lamella; and carrying out at least one second image acquisition, said second acquisition being carried out at a different thickness of the sample relative to the first acquisition so as to obtain a plurality of images corresponding to a section of the sample with a differe

Abstract: Systems, devices, and methods for removing areas of tissue are described. A programmable laser may remove precise areas of tissue while the tissue remains substantially frozen. The laser is programmed in part by analyzing a reference image of a representative tissue section. A software program may receive digital images of test slices. Areas of interest in the image may be selected by a user. The software program can then create and send cut instructions to the programmable laser. The laser may be configured to make perforated cuts to remove the area of interest without melting the removed section.

Abstract: A stain separation system of digital pathology images that performs transforming a digital image from a first color domain to an optical domain to form an optical domain image (ODI), identifying a plane containing two or more basis vector which contain the pixels of the ODI, determining a plurality of orthogonal vector within the identified plane, forming a histogram of the digital image represented by the orthogonal vectors and determining one or more final stain vectors by searching for candidate vectors in the plane that minimize a cost function of the histogram.

Abstract: A whole slide fluorescence digital pathology system is provided that uses a monochrome TDI line scan camera, which is particularly useful in fluorescence scanning where the signal is typically much weaker than in brightfield microscopy. The system uses oblique brightfield illumination for fast and accurate tissue finding and employs a unique double sweep focus scoring and objective lens height averaging technique to identify focus points and create a focus map that can be followed during subsequent scanning to provide autofocusing capability. The system also scans and analyzes image data to determine the optimal line rate for the TDI line scan camera to use during subsequent scanning of the digital slide image and it also creates a light profile to compensate for loss of illumination light due to roll off.

Abstract: A system and method for automatically observing and counting cells without using a stain or a fluorescent material. The system includes an optical microscope having a sensor that provides an electrical signal representative of a field of view. The microscope is motorized so as to allow automatic change of focus. A sample containing cells to be analyzed is provided. No stain or fluorescent substance is used. When the microscope is operated in a deliberately out-of-focus condition, cells appear to have either a bright or a dark spot that can be used to report the number of cells in the sample. The intensity variation detected in images acquired in different focal planes is used to identify cell shapes using image analysis software such as CellProfiler. A result is reported in any convenient format, such as a false color image.