Abstract: The invention pertains to the field of image processing in digital pathology. It notably proposes a method for processing a first digital image, representing a sample in a region, and which image has been acquired from the sample by means of a microscopic imaging system (1) and is stored in a multi-resolution image data structure (80), comprising the steps of:—retrieving (104) a sub-region of the first digital image at a first resolution, —executing (105) a transform function on the retrieved sub-region, the transform function modifying a content of the sub-region according to at least one metric derived from a second resolution representation of the first digital image.

Abstract: Improved systems and methods for the analysis of digital images are provided. More particularly, the present disclosure provides for improved systems and methods for the analysis of digital images of biological tissue samples. Exemplary embodiments provide for: i) segmenting, ii) grouping, and iii) quantifying molecular protein profiles of individual cells in terms of sub cellular compartments (nuclei, membrane, and cytoplasm). The systems and methods of the present disclosure advantageously perform tissue segmentation at the sub-cellular level to facilitate analyzing, grouping and quantifying protein expression profiles of tissue in tissue sections globally and/or locally. Performing local-global tissue analysis and protein quantification advantageously enables correlation of spatial and molecular configuration of cells with molecular information of different types of cancer.

Abstract: A medical image processor and a storage medium are shown. According to one implementation, the medical image processor includes the following. An input unit is used to input a cell shape image and a fluorescent image showing expression of a specific protein. A cell nucleus extracting unit extracts a cell nucleus. A fluorescent bright point extracting unit extracts a fluorescent bright point. A region estimating unit sets a predetermined region. When the set region does not overlap with another, it is estimated to include one cell. When a plurality of the set regions overlap, it is estimated to include a plurality of cells. A feature amount calculating unit calculates a feature amount. A determining unit determines whether each estimated cell region is cancer and determines an expression status in the region based on the calculated feature amount. An output unit outputs a determination result.

Abstract: A culture quality evaluation method comprises: a first step of culturing a pluripotent stem cell under a predetermined culture condition and creating a sample; a second step of imaging a proliferated cell colony in the sample and accordingly capturing an original image; a third step of dividing the original image into smaller images of a predetermined size and calculating standard deviations of pixel values of pixels of the smaller images; and a fourth step of judging whether the sample is an acceptable sample based upon a ratio of a number of the smaller images whose values of the standard deviations are within a predetermined range to a total number of the smaller images.

Abstract: Described herein are materials and methods for evaluating skin quality and providing customized, concierge skin consultation to consumers. In various aspects, the disclosure includes a method comprising detecting polymorphisms in MMP1, SOD2, and GPX1 from a biological sample, calculating a genetic skin score, comparing the genetic skin score to current skin features, and optionally counseling a consumer regarding a skin care regimen customized to enhance immediate skin quality and/or future skin quality.

Abstract: Methods, compositions and kits for determining the developmental potential of one or more embryos or pluripotent cells and/or the presence of chromosomal abnormalities in one or more embryos or pluripotent cells are provided. These methods, compositions and kits find use in identifying embryos and oocytes in vitro that are most useful in treating infertility in humans.

Abstract: A method for automatically rapidly analyzing biological cells includes continuously capturing a plurality of image frames of a suspension including a plurality of biological cells according to a predetermined time interval within a predetermined time using a low-magnification optical image amplification device of a image capture device; transmitting each of the plurality of image frames to an operation processing device; the operation processing device utilizing an image identification technology to detect a number of the plurality of biological cells in an image frame and a static data of each biological cell of the plurality of biological cells according to at least one parameter; and the operation processing device generating a dynamic data of each biological cell in the image frame according to the static data of each biological cell in the image frame and the static data of each biological cell of a previous image frame.

Abstract: A cell image segmentation method includes receiving a cell image, performing a nuclei initialization step to find an internal marker and an external marker to obtain a potential nuclei and a potential cell boundary, calculating a gradient map of the received cell image, performing a filtering step on the gradient map to generate a filtered gradient map, performing a nuclei detection step to obtain a segmented nuclei, and performing a nuclei validation step to obtain a valid nuclei. The nuclei initialization step includes performing a blob detection step to obtain a nuclei candidate, an outlier removal step to obtain the internal marker, a distance transform step to obtain a distance map, and a cell boundary initialization step to obtain the external marker. In another embodiment, a nuclear-to-cytoplasmic ratio evaluation method using the above cell image segmentation method is proposed.

Abstract: A cell analyzing apparatus includes: a first histogram acquiring section which is configured to acquire a first histogram of fluorescence intensities by using a result of a measurement of a number of nuclear stained cells; a second histogram acquiring section which is configured to acquire a second histogram that is normalized based on a fluorescence intensity value indicating a maximum value of the first histogram; a determining section which is configured to determine whether cancer cells exist or not, based on one of the first histogram and the second histogram; and an outputting section which is configured to output a result of the determination performed by the determining section.

Abstract: A computer-assisted method of classifying cytological samples, includes using a processor to analyze images of cytological samples and identify cytological objects of interest within the sample images, wherein the processor (i) displays images of identified cytological objects of interest from the sample images to a reviewer, (ii) accesses a database of images of previously classified cytological objects, and (iii) displays to the reviewer, interspersed with the displayed images of the identified objects of interest from the sample images, one or more images obtained from the database of images of previously-classified objects.

Abstract: A method and device achieves identification on whether a colony on a cultivation container is differentiated or undifferentiated on an occasion of cultivation of multipotent stem cell, and a method and device achieves a rapid culture of undifferentiated multipotent stem cells. Undifferentiated colony containing only undifferentiated multipotent stem cells is identified from other types of colonies by means of the circularity C of the colony in an image-processed taken image of the inside of cultivation container of a multipotent stem cell. More specifically, when a first threshold of the circularity of the colony is C1, and a second predetermined threshold is C2 (C1<C2), a colony satisfying C2?C is determined as the undifferentiated colony, a colony satisfying C1?C<C2 is determined as an undefined colony, and a colony satisfying C<C1 is determined as the differentiated colony.

Abstract: An image processing device 100 divides a hollow organ 50 extracted from a volume image 40 using a plurality of planes 20 including an arbitrary eye vector 23 or a plurality of planes along the centerline of the hollow organ 50, transforms the coordinates of a point inside the hollow organ 50 along a predetermined convex surface set outside the hollow organ 50 on each plane 20, and gives a pixel value of an original position to a corresponding point after the coordinate transformation. Then, a folded volume image is generated by combining the respective planes 20 in a reverse procedure of the division procedure, and a shaded folded three-dimensional image 90 is generated by projecting the folded volume image to a projection surface from the arbitrary viewing direction and is displayed on a display device 107.

Abstract: A blood cell image display apparatus comprising: a classifier for classifying blood cell images, which are obtained by imaging a blood smear prepared from a blood specimen, in accordance with types of blood cells in the blood cell images; an information receiver for receiving information relating to the blood specimen; a display section; and a display controller for determining a type of blood cell as a display object on the basis of the information relating to the blood specimen, and displaying a blood cell image classified as the determined type on the display section, is disclosed. A specimen analyzing system, a blood cell image display method, and a computer program product are also disclosed.

Abstract: Embodiments herein exploit the optical sectioning capability of reflectance confocal microscopy to non-invasively survey the dermal-epidermal junction (DEJ), noting the irregularities associated with malignancy. Methods are provided to aid a clinician in diagnosing melanoma through pattern recognition to extract pertinent diagnostic information from large 3D confocal images. Identifying the combination of pagetoid melanocytes and DEJ breakdown increases the accuracy of detection. A method may be used to process a 3D confocal volume of images taken by a clinician of a suspicious lesion and deduce the depth location z of the first reflective surface (FRS) at each x-y position. This FRS is where the most superficial melanin resides. In this manner, the stratum corneum and epidermis are digitally stripped and no longer distract the clinician from the more diagnostically relevant pigmented cell network. The FRS is putatively either the DEJ for benign nevi or the depth of a pagetoid melanocyte at x,y above the DEJ.

Abstract: Computer implemented methods and data processing apparatus are described for displaying virtual slide images. Images of a plurality of slides are automatically displayed in a first region of a display device at a first magnification. The slides comprise all the slides including material from a same specimen. An image of at least one of the slides is displayed in a second region at a second magnification greater than the first magnification. At least the image displayed in the second region is changed responsive to receiving user input. Methods for automatically determining a slide layout pattern and methods for virtually melding glass slide images into a single image are also described.

Abstract: A cell-image analyzing apparatus includes: a cell imaging system having an imaging optical system and an image sensor, for imaging cells that exist in a vessel; a cell-image analyzer for automatically analyzing a predetermined characteristic quantity on the cells using a cell image captured via the cell imaging system, upon delimiting cell regions; and a cell-contour emphasizing system for automatically emphasizing contour portions of images of the cells that exist in the vessel, which is arranged at a shot position of the cell imaging system.

Abstract: Methods and systems for identifying reticulocytes in a blood sample deposited on a substrate include: illuminating the sample with incident light at two different wavelengths, obtaining a two-dimensional image of the sample corresponding to a first one of the wavelengths, and obtaining a two-dimensional image of the sample corresponding to a second one of the wavelengths; analyzing the images to identify a set of representative red blood cells; determining an area of each of the red blood cells in the set; determining a color value of each of the red blood cells in the set; and, for each one of the red blood cells in the set, identifying the red blood cell as a reticulocyte if the area of the red blood cell exceeds an area cutoff value and the color value of the red blood cell is less than a color cutoff value.

Abstract: A method for acquiring hair characteristic data includes an image acquiring step and a data acquiring step. The image acquiring step acquires a cross-sectional image of a human hair 50, in which plural types of fibrous tissues (ortho cell 52a, para cell 52b) constituting cortex cells 52 contained in the human hair 50 are visualized so as to be distinguishable from each other. The data acquiring step acquires numerical information indicating a distribution state of the visualized plural types of fibrous tissues (ortho cell 52a, para cell 52b) from the cross-sectional image.

Abstract: A medical image processor and storage medium are shown. According to one implementation, a medical image processor includes an input unit, an operation unit, a cell nucleus extracting unit, a fluorescent bright point extracting unit, a feature amount calculating unit, and an output unit. The input unit is used to input a cell shape image showing a shape of a cell and a fluorescent image showing expression of a specific protein as a fluorescent bright point. The operation unit is used to specify an analysis target region. The cell nucleus extracting unit extracts a region of a cell nucleus. The fluorescent bright point extracting unit extracts a fluorescent bright point. The feature amount calculating unit calculates a feature amount showing an expression amount of the specific protein. The output unit outputs the calculated feature amount.

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: The present invention refers to a method for calculating a shape factor indicative of the evenness of the pellucid zone thickness of a biological structure and to a method for evaluating the evenness of the pellucid zone thickness of a biological structure through said shape factor.

Abstract: Methods and systems for digitally enhancing an initial image of a material to which a plurality of stains were previously applied, that generally comprise: unmixing the image into a plurality of individual reconstructed images, each individual image corresponding to one of the stains; estimating a residual image corresponding to the difference between the original image and the reconstructed images; adjusting one or more components of the individual images; mixing the adjusted components using one or more estimated mixing coefficients; and adding the residual image to the mixed adjusted components to generate an enhanced image.

Abstract: A non-invasive method distinguishes between two types of micro-calcification by x-ray imaging in mammography. Two major types of micro-calcifications are found and confirmed by histopathology and they are correlated to benign and malignant breast lesions. Distinguishing between them non-invasively will significantly improve early breast cancer diagnosis. This is based on the fact that these two types of micro-calcifications show opposite absorption and small-angle scattering signals in x-ray imaging. The imaging system, which can record these two signals of the breast tissue simultaneously for instance, an x-ray grating interferometer, can be used to uniquely determine the micro-calcification type. This is expected to be used in mammography to improve early breast cancer diagnosis, increase diagnosis accuracy and decrease the biopsy rate.

Abstract: A method for distinguishing and sorting cells characterized by comprising distinguishing and sorting a specific cell mass or a part of the cells in the cell mass with the use of transmitted light data reflecting the morphological characteristics of the cells such as size and shape optionally together with side-scattering light data reflecting the characteristics of the internal structure of the cells. The part of the cells in the specific cell mass as described above are at the G1 stage or at a part of the M stage in the cell cycle. A part of the cells at the G1 stage are referred to as the left bottom line in an analytical dispersion diagram of the cells wherein the abscissa indicates the transmitted light data, while a part of the cells at the M stage are referred to as the right bottom line in the analytical dispersion diagram of the cells wherein the abscissa indicates the transmitted light data.

Abstract: In various embodiments, methods and apparatus are provided for automated selection of features of cells useful for classifying cell phenotype. The methods include determining a signal-to-noise ratio (S/N) for each of a plurality of pairs of features, rather than S/N for individual features. The approach is capable of quickly identifying a small set of features of imaged cells that are most relevant for classification of a desired cell phenotype from among a very large number of features. The small group of relevant features can then be used to more efficiently and more accurately classify phenotype of unidentified cells.

Abstract: A computer-implemented segmentation method is used to process an image representing a plurality of nuclei. The method is implemented in a computer having a processor and a physical memory. A set of instructions are provided to the processor the physical memory of the computer. The processor is configured by executing the set of instructions in the physical memory so as to automatically segment the image by: thresholding a grey-scale image to create a black and white image; identifying objects in the black and white image and removing objects failing to meet predetermined criteria; extracting objects; and applying an edge detector on the segmented image to identify the edges of the nuclei. Overlapping nuclei are split to improve results.

Abstract: According to one embodiment, storage unit stores three-dimensional function image data concerning a function index of the heart. The extraction unit extracts a myocardial region from the three-dimensional function image data. The normalization unit normalizes the distance between the inner wall and outer wall of the myocardial region with a predetermined numerical value range. The generation unit generates a bull's eye map expressing a spatial distribution of pixel values at positions on the myocardial region by two-dimensional polar coordinates. The positions correspond to predetermined values in the predetermined numerical value range. The display unit displays the bull's eye map.

Abstract: An information processing apparatus includes a memory and a control unit. The memory stores a first image. The control unit divides the first image into a plurality of regions. Further, the control unit calculates a likelihood of an existence of a sample in the plurality of regions thus divided for each of the plurality of regions. Further, the control unit generates an existence map based on the calculated likelihood, the existence map having the plurality of regions classified into first regions, second regions, and third regions. Further, the control unit generates imaging sequence information based on the generated existence map, the imaging sequence information indicating imaging sequences such that the first regions are imaged prior to the second regions and a total movement distance of a stage for imaging the first and second regions becomes minimum.

Abstract: A diagnostic device includes a microscope configured to obtain image data on a plurality of cells and a computing device. The computing device is configured to receive the image data, identify at least a portion of each of the plurality of cells based on the received image data, determine at least one of a value of a morphological parameter for each identified at least a portion of the plurality of cells or a relative organization among the identified at least a portion of the plurality of cells, and calculate statistics for the plurality of cells based on the at least one of the determined values of the morphological parameter or the determined relative organization, the statistics including information suitable for distinguishing metastatic cells from non-metastatic cells. The diagnostic device further includes an output device configured to output the statistics for diagnosis.

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 analyzes 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: Provided is an image processing apparatus capable of analyzing a target sample image with high accuracy in line with a phenomenon occurring in the target sample. The image processing device includes: a dye spectrum storage portion (233) for storing a dye spectrum of a dye used in staining the stained sample; and an arithmetic portion (250) including: a variation characteristic calculating portion (2501) for calculating, based on the stored dye spectrum, a variation characteristic representing either a sharp or gradual change of the dye spectrum in the wavelength direction; and a dye-amount/variation-amount estimating portion (2503) for estimating, based on the stored dye spectrum and the calculated variation characteristic, a variation amount from a pixel value of each pixel forming the stained sample image based on the dye-amount and the variation characteristic, the arithmetic portion analyzing the stained sample image at least based on the variation amount.

Abstract: Disclosed herein is a method of tomographic bright field imaging (TBFI): an optical imaging technique that enables the measurement of cellular refractive index and dry mass density using a standard transillumination optical microscope and software embodying said method.

Abstract: Digital pathology is the concept of capturing digital images from glass microscope slides in order to record, visualize, analyze, manage, report, share and diagnose pathology specimens. The present disclosure is directed to a desktop slide scanner, which enables pathologists to scan slides at a touch of a button. Included is a workflow for reliable imaging, diagnosis, quantification, management, and sharing of a digital pathology library. Also disclosed herein is an analysis framework that provides for pattern recognition of biological samples represented as digital images to automatically quantitatively score normal cell parameters against disease state parameters. The framework provides a pathologist with an opportunity to see what the algorithm is scoring, and simply agree, or edit the result. This framework offers a new tool to enhance the precision of the current standard of care.

Abstract: An image processing apparatus includes a feature value calculating section that calculates a feature value from an image picked up of a living mucous membrane, an extraction section that extracts a structure corresponding to the feature value, and a region division section that divides the structure into partial regions according to a predetermined condition.

Abstract: A method and system are used to analyze the components of a tissue sample by using hyperspectral imaging. The system comprises an image capture module and a hyperspectral image analysis module. The image capture module generates an excitation light beam to illuminate the tissue sample, receives a spectral image induced by the excitation light beam, and converts the spectral image into hyperspectral image data containing continuous spectrum waveforms. The hyperspectral image analysis module performs a linear transformation on the hyperspectral image data to obtain a plurality of linearly-independent continuous spectrum curves and compares the linearly-independent continuous spectrum curves with continuous spectrum data of known components in a database to identify the components in the tissue sample and obtain the types, proportions, and spatial distributions thereof, whereby the physician can diagnose the lesion more accurately.

Abstract: Light is allowed to be incident from above wells provided on a microplate M and the light transmitted to the lower surface is received to obtain an original image of the wells (Step S101). Detection target areas in the original image are specified by an appropriate image processing (Step S102), and peripheral areas as backgrounds surrounding the respective detection target areas are specified (Step S103). By calculating a density value of the detection target area Ri using luminance information of the detection target area Ri and that of the peripheral area Si surrounding this detection target area Ri for each detection target area Ri (Steps S105, S106), the influence of a well wall surface reflected on the background is eliminated.

Abstract: A system and a method are disclosed that determine images with co-occurrence groups of individuals from an image collection. A value of a similarity metric is computed for each pair of images of the image collection, the value of the similarity metric being computed based on a comparison of the number of individuals in common between the images of the pair and the total number of individuals identified in both images of the pair. The collection of images is clustered based on the computed values of the similarity metric. At least one co-occurrence group is determined based on the results of the clustering, where a co-occurrence group is determined as a cluster of images that have a similar combination of individuals.

Abstract: A method for determining a mean cell volume for a blood sample includes: illuminating the sample with incident light at a plurality of illumination wavelengths and obtaining a two-dimensional image of the sample at each of the plurality of illumination wavelengths; identifying a plurality of cells that appear in each of the images; for each one of the plurality of cells, determining an integrated optical density corresponding to each of the plurality of illumination wavelengths; for each one of the plurality of cells, determining a cell volume based on the integrated optical densities corresponding to each of the plurality of illumination wavelengths; and determining the mean cell volume for the blood sample from the cell volumes for each one of the plurality of cells.

Abstract: A sample-image acquisition apparatus includes: an image taking device; a movement control section; and a sample-image acquisition section.

Abstract: A method is described for distinguishing between cancerous and normal human cells. The method includes collecting cells; preparing cells for scanning; scanning of the prepared cells by means of atomic force microscopy; processing of the obtained images through specific algorithms; wherein the algorithms allowing one to identify whether the cell is cancerous or normal.

Abstract: A method of calculating a drop delay in a stream of a flow cytometer. In one embodiment the method includes the steps of determining a widths plot by measuring the width of a stream based on an image of the stream and setting drop delay based on the widths plot. In another aspect the invention relates to a flow cytometer system for automatically calculating drop delay. In one embodiment the flow cytometer system includes means for determining a widths plot based on an image of the stream; and means for calculating drop delay based on the widths plot.

Abstract: Systems and methods for creating and viewing three dimensional digital slides are provided. One or more microscope slides are positioned in an image acquisition device that scans the specimens on the slides and makes two dimensional images at a medium or high resolution. These two dimensional digital slide images are provided to an image viewing workstation where they are viewed by an operator who pans and zooms the two dimensional image and selects an area of interest for scanning at multiple depth levels (Z-planes). The image acquisition device receives a set of parameters for the multiple depth level scan, including a location and a depth. The image acquisition device then scans the specimen at the location in a series of Z-plane images, where each Z-plane image corresponds to a depth level portion of the specimen within the depth parameter.

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: Systems, apparatus, and methods for continuously authenticating individuals are provided. A continuous authentication system receives first biometric authentication information from an individual. The system compares the first biometric authentication information to stored first biometric information to identify the individual and links the identified individual to a device for obtaining second biometric authentication information. The device for obtaining second biometric authentication information continuously receives second biometric authentication information. The continuous authentication system compares the received second biometric authentication information to stored second biometric information that corresponds to the individual to determine if the received second biometric authentication information corresponds to the individual.

Abstract: A computer-based specimen analyzer (10) is configured to detect a level of expression of genes in a cell sample by detecting dots that represent differently stained genes and chromosomes in a cell. The color of the stained genes and the chromosomes is enhanced and filtered to produce a dot mask that defines areas in the image that are genes, chromosomes, or non-genetic material. Metrics are determined for the dots and/or pixels in the image of the cell in areas corresponding to the dots. The metrics are fed to a classifier that separates genes from chromosomes. The results of the classifier are counted to estimate the expression level of genes in the tissue samples.

Abstract: Systems and methods for rapidly analyzing cell containing samples, for example to identify morphology or to localize and quantitate biomarkers are disclosed.

Abstract: The disclosure is directed at a system and method for darkfield imaging system and method for automated cell screening of cells. The system and method acquires multi- or hyperspectral digital darkfield images of cells and then processes the images to obtain measurements which can then be supplied or displayed to a user to analyze.

Abstract: The present invention relates to a method of diagnosis which identifies one or more individual cells and comprises determining at least one of a cell dimension and a cell area, and determining at least one of dark/light cell contrast characteristics, cell area characteristics, cell colour characteristics, cell roughness characteristics, distances between cell nuclei and cell convexity. A computer readable medium, a computer apparatus and a diagnostic system is also provided.

Abstract: An observation apparatus compares a plurality of image information acquired in a specific time by a plurality of image acquisition methods whose image acquisition timings are different, and includes a timer for counting observation time, and a PMT and a CCD whose image information acquisition timings are different. A storage unit stores different image information, when acquired by the PMT and the CCD, by relating each type of the acquired image information to the observation information counted by the timer. A control unit sets a display standard to associate the different types of image information stored in the storage unit, according to the observation time that has been respectively related to these types of image information, and associates the different types of image information according to the time information, on the basis of the set display standard. A monitor displays the image information associated by the control unit.

Abstract: An image identifying device includes a mechanism that sets an evaluation area whose category is to be identified in an in-vivo image; a mechanism that acquires texture components from the evaluation area in the in-vivo image; a mechanism that calculates an evaluation value indicating homogeneity of the texture components; and a mechanism that identifies the category of the evaluation area on the basis of the evaluation value.