Abstract: A portion of imagery data is obtained from a digital slide and a protocol of image analysis/diagnostic tasks is performed on the portion of imagery data by a pathologist or an image analysis module. The result of each task (e.g., success or no success) is recorded and a score is determined for the portion of the imagery data. Multiple portions of imagery data from the digital slide are analyzed and scored and the various scores from the multiple portions of imagery data are calculated to determine an overall score for the digital slide. Regions of the digital slide can be scored separately. Multiple rounds of scoring (by different pathologists and/or different image analysis algorithms) may be employed to increase the accuracy of the score for a digital slide or region thereof.

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: Embodiments disclosed herein include methods, systems, and devices for determining a positive or negative correlation between a clinical outcome and one or more features of biological tissue. An exemplary user interface enables a user to select a clinical outcome and one or more aspects of a displayed field-of-view of biological tissue. Exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of the user-selected aspects of the field-of-view of biological tissue. For example, exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of one or more biological units in the biological tissue.

Abstract: A method for differentiating areas in a series of digital images, the method comprising the steps of: providing a series of images comprising undetermined marker areas; evaluating every image 1n for 1?n?N according to predetermined selection criteria and defining image marker areas as undetermined marker areas fulfilling the predetermined selection criteria; providing a new image 1new; and inserting new image marker areas in the new image 1new, said new image marker areas having the same shape and location as image marker areas present in image 1n but not in image 1n?1, and said new image marker areas being identifiable in 1new by a unique feature. Further, the application discloses a method for visualizing cell populations in tissue sections of a histological sample. Further, the application discloses a method for visualizing three-dimensional distribution of multiple cell populations in a histological sample.

Abstract: A system and method for indirectly measuring calcium ion efflux from a cell of a subject by using manganese ions as a surrogate marker for calcium is disclosed. Manganese ion efflux is measured with a MEMRI T1-mapping method while the calcium-sodium exchanger is inhibited.

Abstract: Method and sequence for locating anomalous features in medical images in which medical images are supplied by an external source such as a CAT or XRAY scan machine or other similar device. A sequence of specific measurements is executed on the supplied data to obtain metrics relating to the images. The metrics are then compared to the corresponding values in an accompanying database resulting in an anomalous/not anomalous determination. Anomalous determinations are presented to the test operator for final analysis along with supplemental historical data. In application to all types of medical imagery, potential anomalies are quickly located resulting in an efficient and more accurate diagnosis.

Abstract: A method is described for correlating microscopy images from a number of modalities in a sub diffraction resolution environment. The method may include receiving a number of datasets that may represent microscopy captures from a number of different modalities. The microscopy captures may contain feature markers that may be used to register a number of data points contained in a dataset with data points from another dataset. Upon registering the data points of the datasets, a combined dataset may be produced and a visual image of the combined dataset may be provided.

Abstract: A method of classifying, with a computer processor, at least one feature of cells from a low contrast, digital image. The method includes generating a contrast-enhanced image by applying a high-pass filter to the low contrast, digital image. The contrast-enhanced image is smoothed with a first low pass filter. A background image, generated from the low contrast, digital image, is subtracted from the smoothed, contrast-enhanced image to form an analysis image. The at least one feature is identified in analysis image.

Abstract: Systems and methods for the detection, analysis, and collection of rare cellular events, wherein rare cellular events are defined by events comprising less than 5% of a total number of cells in a sample. The systems and methods generally include: (1) a flow cell dimensioned so as to permit a flow of a sample through the flow cell at a flow rate greater than 300,000 cells per second; (2) a laser positioned to emit a laser beam directed to the flow cell; (3) one or more deflector components disposed between the laser and the flow cell, wherein the deflector component is configured to affect a position of the laser beam relative to the sample flow; (4) one or more fluorescence emission detectors; and (5) one or more processor configured to detect rare cellular events based on fluorescence emission from cell-binding surface markers introduced into the sample prior to the sample being flowed through the flow cell.

Abstract: In accordance with preferred embodiments of the present invention, a method for imaging tissue, for example, includes the steps of mounting the tissue on a computer controlled stage of a microscope, determining volumetric imaging parameters, directing at least two photons into a region of interest, scanning the region of interest across a portion of the tissue, imaging a plurality of layers of the tissue in a plurality of volumes of the tissue in the region of interest, sectioning the portion of the tissue and imaging a second plurality of layers of the tissue in a second plurality of volumes of the tissue in the region of interest, detecting a fluorescence image of the tissue due to said excitation light; and processing three-dimensional data that is collected to create a three-dimensional image of the region of interest.

Abstract: In a hierarchical display structure, a high layer window contains one or more input images that serve as a window switchover region for switching into a low layer window. Each of the input images is a first correspondence image that has a unique color. When a manipulation device selects one of the input images and performs a determination input to the selected input image in the high layer window being displayed on a screen of a display device, the display on the screen is switched from the high layer window into the low layer window. The low layer window on the screen contains a background image as a second correspondence image that has a color identical to a color of the input image to which the determination input was performed in the high layer window.

Abstract: A computerized method for immunohistochemistry analysis of tissue utilizes digital images of multiple adjacent tissue sections aligned within a computerized software and processed with an algorithm to quantify a two-dimensional IHC signature score for each respective slide image. In various embodiments, the IHC score is performed over several adjacent sections and further processed to produce a three-dimensional IHC quantification referred to as an IHC signature map.

Abstract: Automated islet measurement systems (AIMS) in combination with tissue volume analysis (TVA) software effectively gauges volumetric and size-based data to generate heretofore unavailable information regarding, for example, populations of islet cells, stem cells and related desiderata.

Abstract: A method and apparatus for the imaging of a labeled biological sample. The method comprises illuminating the labeled biological sample, generating members of a time series of images if the labeled biological sample, generating a plurality of difference images between later members of the time series of images of earlier members of the time series of images and combining the plurality of difference images to generate a final image of the labeled biological sample.

Abstract: Systems, devices, and methods are described for identifying, classifying, differentiating, etc., objects. For example a hyperspectral imaging system can include a dark-field module operably coupled to at least one of an optical assembly, a dark-field illuminator, and a hyperspectral imaging module. The dark-field module can include circuitry having one or more sensors operable to acquire one or more dark-field micrographs associated with scattered electromagnetic energy from an object interrogated by the dark-field interrogation stimulus. The hyperspectral imaging module can be operably coupled to the dark-field module, and can include circuitry configured to generate an angular-resolved and spectrally resolved scattering matrix based on the one or more dark-field micrographs of the object.

Abstract: The method is for intracellular counting and segmentation of viral particles or infectious agents in an image. An image is provided that has a plurality of items therein. A radius range of viral particles is determined. Items in the image having a radius within the predetermined radius range are identified. Elliptical items that are formable from the predetermined radius range are determined. The round and elliptical items identified into groups are sorted. The viral particles among the round and elliptical items are identified. For example, the method may be used for intracellular counting and segmentation of siRNA treated human cytomegaloviral particles in TEM images.

Abstract: Systems and methods are provided the autocentering, autofocusing, acquiring, decoding, aligning, analyzing and exchanging among various parties, images, where the images are of arrays of signals associated with ligand-receptor interactions, and more particularly, ligand-receptor interactions where a multitude of receptors are associated with microparticles or microbeads. The beads are encoded to indicate the identity of the receptor attached, and therefore, an assay image and a decoding image are aligned to effect the decoding. The images or data extracted from such images can be exchanged between de-centralized assay locations and a centralized location where the data are analyzed to indicate assay results. Access to data can be restricted to authorized parties in possession of certain coding information, so as to preserve confidentiality.

Abstract: Provided are methods, computer implemented methods, and devices for machine vision. The methods and devices are capable of quantifying the amount of a particular color resulting from a particular stain in a sample stained with multiple agents.

Abstract: A cell is provided that contains a plurality of virus particles. A first image of a first virus particle and a second image of a second virus particle are taken by electron microscopy technology. The first virus particle is characterized as being in a first maturity stage and the second virus particle as being in a second maturity stage. The first image and the second image are transformed to first and second gray scale profiles, respectively, based on pixel data. The first and second gray scale profiles are then saved as first and second templates, respectively. A third virus particle in a third image is identified. The third image is transformed into a third gray scale profile. The third gray scale is compared to the first and second template to determine a maturity stage of the third virus particle.

Abstract: Systems and methods for segmenting images comprising cells, wherein the images comprise a plurality of pixels; one or more three dimensional (3D) clusters of cells are identified in the images; and the 3D clusters of cells are automatically segmented into individual cells using one or more models.

Abstract: Certain aspects of an apparatus and method for method and apparatus for automatic HER2 scoring of tissue samples may include for determining a cancer diagnosis score comprising identifying one or more nuclei in a slide image of a tissue sample, determine one or more membrane strengths in the slide image surrounding each of the one or more nuclei, classifying one or more cells, each corresponding to the one or more nuclei, in a class among a plurality of classes according to the one or more membrane strengths and determining a cancer diagnosis score based on a percentage of cells classified in each of the plurality of classes.

Abstract: Certain aspects of an apparatus and method for automatic ER/PR scoring of tissue samples may include for determining a cancer diagnosis score comprising identifying a positive stained nucleus in a slide image of the tissue sample, identifying a negative stained nucleus in the slide image, computing a proportion score based on number of the positive stained nucleus identified and number of the negative stained nucleus identified and determining the cancer diagnosis score based on the proportion.

Abstract: A system and method for digital staining of an image of biological tissue acquired with the use of multispectral imaging system. The method includes spectral enhancement of the originally-acquired image, which results in differentiation of colorimetrically-similar components of the tissue, and a linear mapping of the spectrally-enhanced image to an estimated target image that represents the spectral response of the tissue manually stained with a target stain.

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: A method of controlling nematode response in a microfluidic environment is provided comprising exposing the nematode to an electric field that induces a nematode response. In one embodiment, a method of sorting a group of nematodes based on a selected parameter is provided comprising the step of exposing the nematodes to an electric field that induces a differential response among the nematodes based on the selected parameter, wherein the differential response functions to separate the nematodes based on the selected parameter. Devices useful to achieve these methods are also provided.

Abstract: An image measurement apparatus includes: an image acquiring unit that acquires a sample image that is an image obtained by capturing an image of a sample; a standard color space converting unit that converts the sample image into a standard sample image that is an image in a standard color space; a color distribution normalizing unit that converts the standard sample image into a normalized sample image by converting pixel values of pixels in the standard sample image to cause a color distribution vector indicating a color distribution of the standard sample image to match a predetermined standard color distribution vector indicating a standard color distribution; and a positive rate acquiring unit that detects positive pixels by performing threshold processing on pixel values of pixels in the normalized sample image, and acquires a positive rate indicating a proportion of the detected positive pixels.

Abstract: An imaging system includes a two-dimensional detector having a plurality of cells wherein each cell is configured to detect energy or signal passing through an object. The imaging system includes a computer programmed to acquire imaging data for the plurality of cells, identify a cell to be corrected, based on the imaging data, interpolate Ix and Iy for the identified cell based on neighbor cells, and calculate local gradients gx and gy between the identified cell and its neighbor cells based on the interpolation. The computer is further programmed to calculate weighting factors wx and wy based on the local gradients, calculate a corrected final value I(0,0) for the identified cell, and correct the identified cell with the corrected final value.

Abstract: A method of counting thrombocytes contained in a sample of blood, the method having the steps: mixing said sample with: fluorescent markers suitable for bonding specifically with the thrombocytes; and an agent for inhibiting activation of said thrombocytes; introducing the sample (E) into a fluidic chamber (CF) having at least one transparent face; acquiring at least one digital image (IN) of said sample by fluorescence microscopy under stationary illumination; and counting the thrombocytes (T) present in said or each image by image processing computer means (O). Apparatus for implementing the method.

Abstract: An image processing apparatus, a method, and a program for allowing cells to be quantitatively observed. A computer obtains a cell membrane image obtained by performing fluorescent observation on a cell membrane of a cell serving as a sample and a tricellular tight junction (tTJ) image obtained by performing fluorescent observation on a protein localized in a tTJ of the cell. The computer derives the size of area of a region of the cell by identifying the region of each cell from the cell membrane image, derives the size of area of the region of the protein localized in the cell from the tTJ image, and dividing the obtained size of area of the region of the protein by the size of area of the region of the cell, thus calculating an index of adhesion strength of the cells. The invention can be applied to an observation system.

Abstract: Among other things, a degree is determined to which values of a feature that characterizes cases correctly predict classes to which cases belong, the degree depending on a combination of at least two factors that include: (a) uncertainty about the values that the feature will have depending on knowledge about classes to which cases belong, and (b) comparison of one or more first values of the feature that are associated with cases that belong to a first class with one or more second values of the feature associated with cases belonging to a second class.

Abstract: A method and system for automatic detection and volumetric quantification of bone lesions in 3D medical images, such as 3D computed tomography (CT) volumes, is disclosed. Regions of interest corresponding to bone regions are detected in a 3D medical image. Bone lesions are detected in the regions of interest using a cascade of trained detectors. The cascade of trained detectors automatically detects lesion centers and then estimates lesion size in all three spatial axes. A hierarchical multi-scale approach is used to detect bone lesions using a cascade of detectors on multiple levels of a resolution pyramid of the 3D medical image.

Abstract: A flow cytometry system includes an inertial particle focusing device including a plurality of substantially parallel microchannels formed in a substrate, each microchannel having a width to height ratio in the range of 2:3 to 1:4, an analyzer disposed adjacent the inertial particle focusing device such that the analyzer is configured to detect a characteristic of particles in the inertial particle focusing device, and a controller connected to the analyzer and configured to direct the detection of the characteristic of the particles.

Abstract: An image processing apparatus includes: a basic shape matching section that extracts, as a structure region, a predetermined structural object included in an image obtained by picking up an image of a mucosal surface of a living body, and matches each of regions resulting from the structure region being divided, the regions each including at least one pixel, with a first region having a first basic shape or a second region having a second basic shape; a feature value calculating section that sequentially sets regions of interest from among the regions matched by the basic shape matching section, and calculates counts of the first regions and the second regions adjacent to each of the regions of interest; and a classification section that classifies the structure region based on a result of the calculation by the feature value calculating section.

Abstract: An image diagnostic processing device includes peripheral region specifying means which specifies a peripheral region connecting to an abnormal candidate region included in an image representing the inside of a subject, and judging means which judges whether the abnormal candidate region is an anatomic abnormal region or not, based on a first feature quantity of the abnormal candidate region and a second feature quantity of the peripheral region.

Abstract: A fluid stream imaging apparatus having either optics for manipulating the aspect ratio or sensing elements configured for manipulating the aspect ratio of an image of the fluid stream. This application may also relate to a system for acquiring images of a portion of a fluid stream at high speeds for image processing to measure and predict droplet delays for individual forming particles.

Abstract: A method and a particle analyzer are provided for determining a particle size distribution of a liquid sample including particles of a lower size range, particles of an intermediate size range, and particles of an upper size range. A dark-field image frame is captured in which the particles of the lower size range and the particles of the intermediate size range are resolved, and a bright-field image frame is captured in which the particles of the intermediate size range and the particles of the upper size range are resolved. Absolute sizes of the particles of the intermediate size range and the particles of the upper size range are determined from the bright-field image frame. Calibrated sizes of the particles of the lower size range are determined from the dark-field image frame by using the particles of the intermediate size range as internal calibration standards.

Abstract: The present invention relates to a method and a system for obtaining and analysing image pairs, obtained as sections of specimen. The invention facilitates registration of two corresponding images, one from each section of the specimen. The invention includes performing a registration process of the two images thereby obtaining a mathematical transformation rule and afterwards using said transformation rule for each image field identified in one image allowing that the corresponding image field in the other image may be identified as well. After the corresponding image pairs have been obtained using the method of the present invention, the sections can be assessed, such as by identifying the counting events for at least one type of object on the image fields within at least one corresponding image pair, optionally using automatic means.

Abstract: An image segmentation embodiment comprises applying a second derivative operator to the pixels of an image, growing a set of contours using seeding grid points as potential contour starting points, determining a contour strength vector for each of the contour pixels, generating a partial ellipse representing an estimated location of an object in the image, dividing the partial ellipse into a plurality of support sectors with control points, determining a contour strength and position for each contour, adjusting a position of each sector control point based on the contour positions weighted by the contour strengths of the contours centered in the respective sector, fitting the partial ellipse to the adjusted positions of the control points, and generating a segmentation mask of the object based on the partial fitted ellipse.

Abstract: An image segmentation embodiment comprises generating a start model comprising a set of model points approximating an outline of an object in an initial image, smoothing the image at a first smoothing level, generating a curvature image by applying a second derivative operator, locating second derivative local maxima in the curvature image that are orthogonal to a respective model point and within a search region having a first boundary on one side of the start model and a second boundary on an opposite side of the start model, generating a set of contours, shifting the start model to an outer boundary of the contours, and generating a segmentation mask of the object based on the shifted start model.

Abstract: Provided is a cell analysis method in a cell analysis device D that uses an optical path length image of a cell colony formed of a large number of cells to analyze the cell colony, the method comprising: acquiring the optical path length image of the cell colony by an acquisition unit of the cell analysis device; extracting a circular shape corresponding to a cell nucleus of the cell in the acquired optical path length image by an extraction unit of the cell analysis device extracts; comparing an inner optical path length of the extracted circular shape and an outer optical path length of the extracted circular shape by a comparison unit of the cell analysis device extracts; and analyzing the cell colony based on the comparison result by analysis unit of the cell analysis device.

Abstract: A system and method are provided for measuring dynamic phenomena in a biological, chemical or physical sample, including the measurement of Ca2+ transients in a living system. The system and method include measuring dynamic phenomena in an in vitro cardiac cell culture system. Computing system environments and computing systems for implementing the method are provided.

Abstract: A computerized image guided biological cellular process progressive selection method receives at least one state cell image. A state cell region recognition is performed using the state cell image to generate state cell region output. A state cell measurement is performed using the state cell region to generate at least one state cell feature output. A state cell decision is performed using the state cell feature to generate state cell selection decision output. The selected cell is progressively selected in at least one follow-on states by its image guided state cell selection method. The method further includes at least one additional image acquired in a later frame of same state and state cell feature includes temporal features of growth patterns.

Abstract: The disclosure features methods and systems that include a detector configured to obtain multiple images of a sample stained with first and second stains, where the first and second stains have similar spectral absorption and emission profiles, and an electronic processor configured to decompose the multiple images into an unmixed image set, where the unmixed image set includes a first unmixed image corresponding to the first stain and a second unmixed image corresponding to the second stain, and identify nuclear regions in the sample based on the first unmixed image and identify cytoplasm regions in the sample based on the second unmixed image.

Abstract: Multimodal or multispectral images of cells comprising a population of cells are simultaneously collected. Photometric and/or morphometric image features identifiable in the images are used to identify differences between first and second populations of cells. The differences can include changes in a relative percentage of different cell types in each population, or a change in a first type of cell present in the first population of cells and the same type of cell in the second population of cells. The changes may be indicative of a disease state, indicative of a relative effectiveness of a therapy, or indicative of a health of the person from whom the cells populations were obtained.

Abstract: An image-based biomarker is generated using image features obtained through object-oriented image analysis of medical images. The values of a first subset of image features are measured and weighted. The weighted values of the image features are summed to calculate the magnitude of a first image-based biomarker. The magnitude of the biomarker for each patient is correlated with a clinical endpoint, such as a survival time, that was observed for the patient whose medical images were analyzed. The correlation is displayed on a graphical user interface as a scatter plot. A second subset of image features is selected that belong to a second image-based biomarker such that the magnitudes of the second image-based biomarker for the patients better correlate with the clinical endpoints observed for those patients. The second biomarker can then be used to predict the clinical endpoint of other patients whose clinical endpoints have not yet been observed.

Abstract: A method performed by one or more processing devices includes retrieving data for a protein in a tissue type in a first state and for the protein in the tissue type in a second state; determining, based on the retrieved data, first features of the protein in the tissue type in the first state; determining, based on the retrieved, second features of the protein in the tissue type in the second state; and identifying, based on the first features and the second features, that a location of the protein in the tissue type in the first state differs from a location of the protein in the tissue type in the second state.

Abstract: Disclosed herein are generally to methods and systems that facilitate imaging of cells on a substrate and more particularly to pre-implantation (in vitro) and post-implantation (in vivo) imaging of cell-seeded substrates implanted in target tissues in the context of stem cell therapy.

Abstract: A method for training a classifier to be operative as an epithelial texture classifier, includes obtaining a plurality of training micrograph areas of biopsy tissue and for each of the training micrograph areas, identifying probable locations of nuclei that form epithelia, generating a skeleton graph from the probable locations of the nuclei that form the epithelia, manually drawing walls on the skeleton graph outside of the epithelia to divide the epithelia from one another, and manually selecting points that lie entirely inside the epithelia to generate open and/or closed geodesic paths in the skeleton graph between pairs of the selected points. Data is obtained from points selected from the walls and the paths and applied to a classifier to train the classifier as the epithelial texture classifier.

Abstract: A method of operating an instrument that is a macroscope, microscope, or slide scanner is provided where the instrument has a larger dynamic range for measurement than a dynamic range required in the final image of a specimen. In the method, data is measured from a specimen using the instrument, and the dynamic range of the measured data is contracted in the final image file during scanning.

Abstract: The present invention relates generally to improved methods of defining areas or compartments within which biomarker expression is detected and quantified. In particular, the present invention relates to automated methods for delineating marker-defined compartments objectively with minimal operator intervention or decision making. The method provides for precise definition of tissue, cellular or subcellular compartments particularly in histological tissue sections in which to quantitatively analyzing protein expression.