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.

Abstract: Image blurring of a mass spectrum image obtained by the signal intensity for each mass/charge ratio from the obtained two-dimensional mass spectrum is reduced by image restoration using a blurring function. The blurring function expresses a two dimensional distribution of transferred energy related to the distance from a point of primary ion incidence limited by a region exceeding desorption energy of a molecule.

Abstract: Provided is an information processing apparatus including a detection unit configured to detect a failure requiring reimaging relating to an image captured using a digital microscope by evaluating the image, and a generation unit configured to, if the failure was detected by the detection unit, generate setting information for setting an imaging condition for during reimaging.

Abstract: A system for detecting post-operative retained foreign bodies has a data storage unit adapted to receive and store a reference image of a surgical object, and a data processor in communication with the data storage unit. The data processor is configured to receive an image of an internal region of a patient and to receive the reference image from the data storage unit, and the data processor is configured to perform operations based on an algorithm to compare the reference image to at least a portion of the image of the internal region of the patient and determine whether a retained foreign body is present in the patient.

Abstract: A method of segmenting a digital image of biological tissue includes accessing a ranking model calculated from training data representing shapes of conforming and non-conforming biological unit exemplars. The ranking model may include support vectors defining a hyperplane in a vector space. The method further includes accessing image data representing the digital image, identifying a first shape and a set of second constituent shapes in the digital image, wherein the first shape comprises a union of the set of second constituent shapes, determining a rank of a first data point in the image data corresponding to the first shape and a rank of a second data point in the image data corresponding to the set of second constituent shapes into the vector space, and segmenting the digital image using the first shape or the set of second constituent shapes based on which data point has a greater respective rank.

Abstract: A method is disclosed including: receiving raw image data corresponding to a series of raw images; processing the raw image data with an encoder to generate encoded data, where the encoder is characterized by an input/output transformation that substantially mimics the input/output transformation of one or more retinal cells of a vertebrate retina; and applying a first machine vision algorithm to data generated based at least in part on the encoded data.

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: An image processing device determines the degree of activity of a cell during cell viewing. An imaging device captures first and second images of a cell under observation. After aligning the rotational angle orientations on the image plane of the cell under observation that is included in the images, a correlation value or difference of intracellular texture feature values in the first image and second image, is sequentially computed. A time series variation of the computed correlation value or difference is then derived, and the degree of activity of the cell under observation is detected based on the state of variation.

Abstract: A method for determining a location of a target includes, at a first location, determining first location coordinates of a measuring device using one or more GNSS signals, determining a first gravitational direction, and capturing a first image using the camera. The method also includes, at a second location, determining second location coordinates of the measuring device, and capturing a second image. The method further includes determining a plurality of correspondence points between the first and second images, determining a first plurality of image coordinates for the plurality of correspondence points in the first image, determining a second plurality of image coordinates for the plurality of correspondence points in the second image, and determining the location of the target using at least the first plurality of image coordinates, the second plurality of image coordinates, and the first gravitational direction.

Abstract: Computerized image guided control method uses image quantification to dynamically monitor and control the cell generation process. The method acquires images during the cell generation steps and uses computer image analysis to automatically quantify the results of the cell generation steps. In one embodiment, the quantified results from the image analysis are used to determine the readiness of the cell generation step. In another embodiment, a remedial recovery sub-step for the cell generation step is also guided by the imaging results. In yet another embodiment, when a cell generation step is determined to have failed, the cell generation process is early terminated based on image guided decision.

Abstract: There is provided a measurement apparatus including an objective lens, a stage, a setting unit, and a controller. The stage is configured to support a sample vessel in which a plurality of wells each containing a sample are arranged and to define relative positions of the sample vessel and the objective lens. The setting unit is configured to determine whether to set each of the plurality of wells to be a measurement target and set the measurement target. The controller is configured to control the stage such that a well determined to be the measurement target by the setting unit and the objective lens face each other.

Abstract: The present disclosure provides a method of determining a reference depth level within a cell sample. The method comprises obtaining data representative of a series of images captured by performing a depth scan of the cell sample using a digital microscope, the series of images being associated with a series of depth levels of the cell sample; processing said data for detecting at least one depth level corresponding to a drop in image contrast; and identifying the detected depth level as the reference depth level.

Abstract: Disclosed is a method and a system for obtaining and analyzing 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: A method for analysis of 2-D gel images obtained using electrophoresis. More particularly, a molecular block-matching method for establishing the correspondence between protein spots in a diagnostic-test image and protein spots in a reference image. Individual protein spot matching is performed, thereby removing the need for alignment of the entire reference and test images and permitting automatic labeling of individual protein spots. The method for analysis of 2-D gel images is fully automated, thus making it ideally suited for protein information retrieval systems.

Abstract: A method and systems for cloud-based digital pathology include scanning received slides that include a pathology sample to produce a sample image in a shared memory, analyzing the sample image using one or more execution nodes, each including one or more processors, according to one or more analysis types to produce intermediate results, transmitting some or all of the sample image to a client device, further analyzing the sample image responsive to a request from the client device to produce a final analysis based on the intermediate results, and transmitting the final analysis to the client device.

Abstract: A home healthcare management system wherein a patient conducts self diagnoses and self testing, and manages their own medical records at home. A digital microscope is utilized as part of the system that is smaller, of lower cost, faster, of a higher dynamic range, and has a higher resolution than conventional microscopes. The microscope consists of an illumination source, a spatial sub-sampling device and a detector device. The digital microscope provides a vectored method of collecting images from a digital microscope that is independent of the optical resolution, and a slide based coordinate system, and a method of displaying images and communicating such images over the Internet in a file format that does not require a header or prior knowledge of magnification, coordinate system, or tiling structure. The system further includes an interface for physiological monitoring devices and a connection to the Internet for more comprehensive services.

Abstract: Digital evaluation of cellblock preparations to determine the type and extent of disease in order to identify the best approach for treatment without the need for additional testing or sampling.

Abstract: A system for processing an image comprises a region detector (1). The region detector comprises an artifact detector (7) for detecting a region comprising an artifact in the image. The system comprises a parameter determining unit (2) for determining a parameter, based on a portion of the image excluding the detected region. The system comprises an image processing module (3) for processing the image, using the derived parameter. The system comprises a display unit (5) for displaying the processed image with an indication of the detected region. The parameter determined by the parameter determining unit (2) can comprise a normalization parameter, and the image processing module (3) can be arranged for performing a normalization of the image according to the normalization parameter.

Abstract: An automated identification of the types of white blood cells in a blood sample facilitates the manual identification of cancerous or other abnormal blood cells in the sample. Classifiers are predetermined for each type of white blood cell and subsequently used to automatically process images of cells in a sample stained with a nuclear dye or stain. The classifiers each comprise a linear weighted combination of morphometric and photometric features previously selected for white blood cells that were identified using monoclonal antibody stains. Red blood cells and excess fluid are removed from a sample being processed upstream of an imaging region of the imaging system. A plurality of different types of images are produced for each cell by the imaging system enabling automated identification of the white blood cells. Images of any cells not thus identified are manually reviewed to detect cancerous or abnormal cells.

Abstract: A computer-based method for the development of an image analysis protocol for analyzing image data, the image data containing images including image objects, in particular biological image objects such as biological cells. The image analysis protocol, once developed, is operable in an image analysis software system to report on one or more measurements conducted on selected ones of the image objects. The development process includes defining target identification settings to identify at least two different target sets of image objects, defining target identification settings to identify at least two different target sets of image objects, and defining one or more measurements to be performed using said pair-wise linking relationship(s).

Abstract: A computer implemented method of analyzing tissue features based on multiplexed biometric images includes storing a data set including cell profile data and an assessment associated with a field of view or a patient. The cell profile data includes biomarker expression intensity data for at least one cell feature. The method includes normalizing the biomarker expression intensity data for each field of view. The method includes determining a plurality of positive cell percentages for a first cell feature for each field of view or for each patient based on a plurality of normalized expression cutoffs for all fields of view. The method further includes correlating positive cell percentages with assessments for each field of view or each patient. The method also includes identifying a combination of a cell feature for expression of a biomarker and a normalized expression cutoff that most closely correlate the positive cell percentage with the assessment.

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 a method and apparatus for efficiently handling a large amount of data collected by an imaging mass analysis to present significant information for the analysis of the tissue structure of a biological sample or other objects in an intuitively understandable form for analysis operators. For each pixel 8b on a sample 8, a mass-to-charge ratio m/z(i) corresponding to the maximum intensity MI(i) in a mass spectrum is listed, and the largest value MII of the maximum intensities of all the pixels are extracted. A color scale corresponding to the intensity values within a range of 0 to MII is defined. For each pixel, the maximum intensity MI is compared with the color scale to assign a color to that pixel. A mapping image with the pixels shown in the respective colors is created and displayed.

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: The method according to the invention generates a color decomposition of histological tissue image data into density maps, where each density map corresponds to the portion of the original image data that contains one stain/tissue combination. After a microscope captures histological tissue image data from a tissue sample that has been stained with at least one stain, the said stain or stains being light absorbent, the method derives from the histological tissue image data a color mixing matrix with the columns of the matrix being color reference vectors. From this mixing matrix the method derives a density map, when the mixing matrix is well-conditioned, by applying a pseudo-inverse of the mixing matrix to the optical density data, and when the mixing matrix is medially-conditioned, by applying a piece-wise pseudo-inverse of the mixing matrix to the optical density data. The method according to the invention also generates stain/tissue combination efficacy measures.

Abstract: Systems and methods of use to facilitate classification of cytological specimens are discussed. The system acquires or imports image data of a cytological specimen. The imported image data may include, or the system may otherwise perform an image analysis to identify one or more objects of interest in a respective specimen image dataset, including feature attributes for the identified objects. The system analyzes the feature attributes by predetermined criteria and/or optionally with user inputted criteria. The system includes an analysis tool that assists the user in identifying cytologically abnormal objects, if present in a particular specimen, by manipulating and viewing images of objects selected as a function of feature attributes. More generally, the analysis tool aides the user to find, extract, and display abnormal objects from within a large dataset of images and facilitates navigation through large amounts of image data and enables the efficient classification of the entire specimen.

Abstract: A cell stethoscope 1 comprises a sample image input section 31 for inputting image information of a cell, an image display part 50 for displaying the image information to an observer, an area designation part 40 for designating a fixed area included in the image information in response to an operation carried out by the observer according to the image information displayed by the image display part 50, a frequency conversion section 32 for frequency-converting vibration information of the cell in the fixed area designated by the area designation part 40 into sound information, and a sound output part 60 for outputting the sound information frequency-converted by the frequency conversion section 32 to the observer.

Abstract: A teachable object contour mapping method for region partition receives an object boundary and a teaching image. An object contour mapping recipe creation is performed using the object boundary and the teaching image to generate object contour mapping recipe output. An object contour mapping is applied to an application image using the object contour mapping recipe and the application image to generate object contour map output. An object region partition using the object contour map to generate object region partition output An updateable object contour mapping method receives a contour mapping recipe and a validation image. An object contour mapping is performed using the object contour mapping recipe and the validation image to generate validation contour map output. An object region partition receives a region mask to generate validation object region partition output. A boundary correction is performed using the validation object region partition to generate corrected object boundary output.

Abstract: The present invention pertains to an apparatus for holding cells. The apparatus comprises a mechanism for incubating cells having a dynamically controlled environment in which the cells are grown, which are maintained in a desired condition and in which cells can be examined while the environment is dynamically controlled and maintained in the desired condition. The apparatus also comprises a mechanism for determining the state of the cells. The determining mechanism is in communication with the incubating mechanism. The present invention pertains to a method for holding cells. The method comprises the steps of incubating the cells in a dynamically controlled environment which is maintained in a desired condition and in which the cells can be examined while the environment is dynamically controlled and maintained in the desired condition. Additionally, there is the step of determining the state of the cells.

Abstract: An image processing method generates two-dimensional images, each of which are respectively in accordance with left and right breasts of a subject using three-dimensional image data of the left and right breasts. A comparison two-dimensional combined image is generated, wherein the left and right breast images are disposed symmetrically. The comparison two-dimensional combined image is displayed on a display unit.

Abstract: The invention relates to a method for detecting clusters of biological particles (12) on a surface (11), comprising steps that involve: a. determining (E1) a topographical representation (20) of said surface; and b. detecting (E3, E4), on said topographical representation, at least one contour defining a region that is likely to correspond to a cluster of biological particles.

Abstract: Systems, devices, and methods are described for providing a monitor or treatment device configured to, for example, detect hemozoin, as well as to monitor or treat a malarial infection.

Abstract: Apparatus, methods, and other embodiments associated with objectively predicting biochemical recurrence (BCR) with cell orientation entropy (COrE) are described. One example apparatus includes a set of logics that associate directional disorder with a risk of biochemical recurrence in a tissue. A first logic detects a cell in the tissue, segments boundaries of the cell, and calculates a cell direction for the cell. A second logic constructs a localized sparsified subgraph whose nodes represent centroids of the cells, defines pairwise spatial relationships between the cells, and constructs a directional co-occurrence matrix based on the spatial relationships. A third logic derives second order statistical features from the co-occurrence matrix, and produces a BCR risk score as a function of the second order statistical features. The second order statistical features include the entropy of the directional organization of the cells.

Abstract: In an example embodiment, may be embodied in a a data analysis apparatus comprises a control unit configured to provide data representative of a three dimensional image, the three dimensional image including at least a three dimensional coordinate space which includes at least one plane that divides the three dimensional coordinate space into at least two regions, a display unit configured to produce the three dimensional image based on the data representative of the three dimensional image, and an input unit configured to provide data representative of at least one of a movement and a position of the at least one plane. In other example embodiments, the present disclosure may be embodied in a data analysis server, a data analysis system, and/or a computer readable medium.

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: An image processing device can explicitly distinguish cells to be observed from cells other than those to be observed with a simple configuration. To this end, the image processing device includes a color information obtaining part obtaining at least hue from color information of each pixel of a color image, a detecting part detecting a mode value of the hue on a color space, a range setting part setting a predetermined range on the color space including the mode value of the hue detected by the detecting part as a target range, a changing part changing hue of a pixel included in the target range by virtually performing extension on the target range, and an information converting part converting color information of a pixel having hue not included in the target range into color information indicative of an achromatic color.

Abstract: A method of processing data associated with fluorescent emissions from a microfluidic device. The method includes performing an auto-focus process associated with a first image of the microfluidic device and performing an auto-exposure process associated with the first image of the microfluidic device. The method also includes capturing a plurality of images of the microfluidic device. The plurality of images are associated with a plurality of thermal cycles. The method further includes performing image analysis of the plurality of captured images to determine a series of optical intensities and performing data analysis of the series of optical intensities to provide a series of change in threshold values.

Abstract: A phase distribution measurement method inside a biological sample includes taking in an optical image of the sample formed by a microscope to form a plurality of images with different image contrasts; calculating a component corresponding to phase distribution of the sample and a component corresponding to other than the phase distribution, and dividing the component corresponding to the phase distribution by the component corresponding to other than the phase distribution to forma normalized phase component image; breaking down the phase component image into a plurality of frequency components; performing a deconvolution process to each of the frequency components using an optical response character corresponding to each, and calculating phase distribution of a refraction component and phase distribution of a structure component; and calculating phase distribution of the sample by compounding the phase distribution of the refraction component and the phase distribution of the structure component.

Abstract: A method performed by one or more processors, includes: receiving an image to be segmented into one or more representations of one or more biological structures; accessing data representing a set of biological structures that are derived from other biological structures delineated in a training image, wherein the training image is associated with a level of modality that corresponds to a level of modality associated with the image to be segmented; computing a normalized cross correlation of the received image against one or more of the biological structures in the set of biological structures; generating, based on computing, seed data representing an estimate of a spatial organization of the one or more biological structures in the received image; and segmenting, based on a normalized cross correction of the received image to the seed data, the received image into the one or more representations of the one or more biological structures.

Abstract: The methods, devices, and systems may allow a practitioner to obtain information regarding a biological sample, including analytical data, a medical diagnosis, and/or a prognosis or predictive analysis. The method, devices, and systems may provide a grade or level of development for identified diseases. In addition, the methods, devices and systems may generate a confidence value for the predictive classifications generated, which may, for example be generated in a format to show such confidence value or other feature in a graphical representation (e.g., a color code). Further, the methods, devices and system may aid in the identification and discovery of new classes and tissue sub-types.

Abstract: A compact and light-weight lens-free platform to conduct automated semen analysis is disclosed. The device employs holographic on-chip imaging and does not require any lenses, lasers or other bulky optical components to achieve phase and amplitude imaging of sperm a relatively large field-of-view with an effective numerical aperture of approximately 0.2. A series of digital image frames is obtained of the sample. Digital subtraction of the consecutive lens-free frames, followed by processing of the reconstructed phase images, enables automated quantification of the count, the speed and the dynamic trajectories of motile sperm, while summation of the same frames permits counting of immotile sperm.

Abstract: A specimen processing system comprising: a blood cell counting apparatus; and a blood cell image classifying apparatus, wherein the blood cell image classifying apparatus comprises a controller to carry out operations, comprising: receiving a plurality of first count results of a predetermined type of the blood cell by the blood cell counting apparatus; obtaining a plurality of second count results of the predetermined type of the blood cell on the basis of the blood cell image; storing the plurality of the first count results and the second count results; reading at least one of the first count results, and at least one of the second count results obtained from a blood specimen corresponding to the first count result; generating and outputting a quality control screen on the basis of the read first count result and the read second count result. A blood cell image classifying apparatus is also disclosed.

Abstract: Techniques described herein are generally related to high resolution image recovery of objects from digital holograms. The various described techniques may be applied to methods, systems, devices or combinations thereof. Some described methods for recovering an image may include receiving reference beam data that corresponds to a reference interference pattern and receiving hologram data corresponding to an object. The method may also include applying a cost function to the hologram data and the reference beam data to determine the object image data associated with the object. The cost function may include a smoothness constraint applied to the object image data.

Abstract: Embodiments of the invention relate to a constructing a gene interaction network. Tools are provided to compute a gene relationship measure based upon cellular images, and to rank image collections having a similar morphology. The ranking is based upon capturing similarity within the ranked collection by modeling a three dimensional shape of a cellular image stack. The graph is constructed for related images stacks. Nodes in the graph represent genes, and edges drawn between the nodes represent corresponding image stacks in a commonly ranked list. Accordingly, the graphical representation mathematically and visually connects respective genes.

Abstract: The present disclosure provides methods, systems, and computer-readable storage media that can be used to image an unstained sample. Traditionally histopathology and immunohistochemistry methods use stains or dyes in combination with microscopy (or other detection methods) to detect cells and cellular structures, such as proteins. However, the disclosed methods do not require the use of such stains and dyes. The disclosed methods can include obtaining a spectroscopic image (e.g., infrared (IR) imaging data) of the sample, analyzing the resulting spectroscopic image to reduce the dimensionality of the spectroscopic image, comparing the reduced spectroscopic image compared to a control (e.g., by using an appropriately trained algorithm) and generating an output computed stain image from the reduced IR spectra, thereby imaging the sample without the use of stains or dyes.

Abstract: A method and apparatus for determining a cell volume of a red blood cell is provided. The method includes the steps of: a) depositing a sample into an analysis chamber, the chamber defined by an first panel interior surface, a second panel interior surface, and a known or determinable height, which height is such that at least one red blood cell subject to a sphering agent assumes a partially compressed spherical shape in contact with the interior surfaces; b) imaging the at least one partially compressed spherical red blood cell contacting the interior surfaces, and producing image signals; c) determining a radius of the partially compressed spherical red blood cell from the image signals; and d) determining a volume of the imaged red blood cell using the determined radius.

Abstract: Automated AIF/VOF identification is useful in connection with providing rapid and automatic quantitative imaging results. Examples include CBF (cerebral blood flow) and CBV (cerebral blood volume) perfusion maps. In the present work, AIF/VOF regions of images are identified by making use of a predefined anatomic vasculature template to provide numerical weighting values for voxels. A score is computed for each voxel that includes normalized signal fit parameters and the numerical weighting. AIF/VOF voxels are identified as N voxels having the highest score, where N can depend on the image resolution.

Abstract: An image analysis system for determining cancerous cells includes an acquisition module, an image capturing module and a multi-spectral image reproduction module. A method for determining cancerous cells includes a spectral database establishing procedure of cancerous cells and a cell determining procedure of multi-spectral image reproduction. The spectral database establishing procedure includes a penetration spectrum analysis step and a database establishing step. The cell determining procedure is based on the cancerous spectrum database and includes an image capturing step, a cell location contouring step, a penetration spectrum analyzing step, a classifying step, a color gaining step, an image reproduction step and a cell determining step.

Abstract: A computer system for analyzing a specimen processing workflow in a pathology laboratory including a display and a processor configured to provide a first interface, a second interface, and a third interface to the display, receive, via the first interface, a first set of parameters associated with an existing specimen processing workflow in a pathology laboratory, the first set of parameters including a workflow process and a workflow scale, and determine, based on the first set of parameters, current performance data of the existing specimen processing workflow having an associated current cost information and current time utilization.

Abstract: Methods and systems for tissue classification of a tissue sample are provided. The methods and systems transform the tissue image data to a biomarker enhanced tissue network (BETN) such that an individual cell or a sub-cellular structure in the tissue image data corresponds to a node in the BETN, define a feature vector based on a feature set representative of a tissue type of interest, cluster nodes of the BETN based on a similarity criterion of one or features of the feature vector, and classify the nodes in the tissue image data based on the grouping of the nodes of the BETN.