Abstract:
The present disclosures relates to a method of detecting, classifying, and counting dots in an image of a tissue specimen comprising detecting dots in an image of the tissue sample that meet criteria for absorbance strength, black unmixed image channel strength, red unmixed image channel strength, and a difference of Gaussian threshold, wherein the detected dots correspond to in situ hybridization signals in the tissue samples; classifying the detected dots as belonging to a black in situ hybridization signal or to a red in situ hybridization signal; and calculating a ratio of those dots belonging to the black in situ hybridization signal and those belonging to the red in situ hybridization signal.
Abstract:
The disclosure relates to devices, systems and methods for image registration and annotation. The devices include computer software products for aligning whole slide digital images on a common grid and transferring annotations from one aligned image to another aligned image on the basis of matching tissue structure. The systems include computer-implemented systems such as work stations and networked computers for accomplishing the tissue-structure based image registration and cross-image annotation. The methods include processes for aligning digital images corresponding to adjacent tissue sections on a common grid based on tissue structure, and transferring annotations from one of the adjacent tissue images to another of the adjacent tissue images.
Abstract:
The invention discloses an automated flow cytometry analysis method and system. An automated method and system are provided for receiving an input of flow cytometry data and analyzing the data using a hierarchical arrangement of analytical elements, each of which utilizes a support vector machine to automatically classify the data into different subpopulations to recognize a pattern within the data. The pattern may be used to generate a diagnostic prediction for a patient or to identify patterns within samples collected from multiple subjects.
Abstract:
Disclosed are a cell determination device, a cell determination method, and a cell determination program capable of objectively determining a state of a cell with high accuracy. The cell determination device includes: a cell information acquisition unit 31 that acquires information relating to a proliferation rate of a cell and information relating to a movement distance of the cell per unit time based on plural cell images obtained by imaging the cell in a time series manner; and a determination unit 32 that determines a state of the cell based on the information relating to the proliferation rate and the information relating to the movement distance.
Abstract:
Systems and methods are used to display cell structures of a biological cell. A plurality of cell structures of a biological cell is stored and for each cell structure of the plurality of cell structures one or more stain colors are stored. A selected cell structure is received from an input device. One or more stain colors of the selected cell structure are retrieved. The one or more stain colors of the selected cell structure are displayed. A selected stain color is received from the input device. The selected cell structure is displayed in the selected stain color in an exemplary cell image. Further, a three-dimensional image of a biological cell is stored. The three-dimensional image is displayed on a display that includes a touch screen. A movement selection is received from the touch screen. The three-dimensional image is displayed on the display according to the movement selection.
Abstract:
An imaging system and method for microbial growth detection, counting or identification. One colony may be contrasted in an image that is not optimal for another type of colony. The system and method provides contrast from all available material through space (spatial differences), time (differences appearing over time for a given capture condition) and color space transformation using image input information over time to assess whether microbial growth has occurred for a given sample.
Abstract:
A three-dimensional image reconstruction method capable of analyzing a three-dimensional structure of membrane proteins present within a lipid membrane is offered. A three-dimensional image reconstruction method associated with the present invention comprises the steps of: obtaining a first transmission electron microscope image of a sample containing the membrane proteins present within a lipid membrane, the image having been taken by illuminating an electron beam on the sample from a direction tilted relative to a line normal to the membrane surface of the lipid membrane (step S10); obtaining a second transmission electron microscope image of the sample taken by illuminating the electron beam on the sample perpendicularly to the membrane surface of the lipid membrane (step S12); identifying orientations of the membrane proteins of the first transmission electron microscope image on a basis of the second transmission electron microscope image (step S14); and analyzing a three-dimensional structure of the membrane proteins from the first transmission electron microscope image on a basis of information about the identified orientations of the membrane proteins (step S18).
Abstract:
Provided herein are systems and methods for identification of gemstones. The gemstones can be identified without removing the gemstones from an object in which the gemstones can be set. The gemstones can be imaged and image analysis can quantify one or more external and/or internal characteristics of the gemstone. The quantification of the one or more external and/or internal characteristics of the gemstone can be compared to a previous characterization to positively identify the gemstone.
Abstract:
The subject disclosure provides systems and methods for determination of Area of Interest (AOI) for different types of input slides. Slide thumbnails may be assigned into one of five different types, and separate algorithms for AOI detection executed depending on the slide type. Slide types include ThinPrep (RTM) slides, tissue micro-array (TMA) slides, control HER2 slides with 4 cores, smear slides, and a generic slide. The slide type may be assigned based on a user input. Customized AOI detection operations are provided for each slide type. If the user enters an incorrect slide type, operations include detecting the incorrect input and executing the appropriate method. The result of each AOI detection operations provides as its output a soft-weighted image having zero intensity values at pixels that are detected as not belonging to tissue, and higher intensity values assigned to pixels detected as likely belonging to tissue regions.
Abstract:
[Object] To provide an information processing apparatus, an information processing method, and an information processing program that allow a user to easily adequately move a display area by guiding a browsed part when a needle biopsy image is browsed. [Solving Means] An information processing apparatus includes: a storage unit to store a pathological image of a specimen and guide information along the center line of a shape of the specimen in the pathological image; a display control unit to display at least a part of the stored pathological image, as an observation image, on a screen; an input unit to receive an instruction for changing a range on the pathological image of the observation image displayed on the screen, from a user; and a control unit to calculate the range on the pathological image of the observation image based on the instruction and the stored guide information.