An inspection apparatus includes a specimen stage configured to retain a specimen, at least three imaging devices arranged in a triangular array positioned above the specimen stage, each of the at least three imaging devices configured to capture an image of the specimen, one or more sets of lights positioned between the specimen stage and the at least three imaging devices, and a control system in communication with the at least three imaging devices.

Aligning multiple 3D images of an object can be difficult when the representative datasets (images) are large. An exemplary aspect of this technology teaches a technique to subdivide the images and use the alignments between the subdivided images to determine the alignment between the complete datasets.

This document describes methods, systems and computer program products directed to imaging blood cells. The subject matter described in this document can be embodied in a method of classifying white blood cells (WBCs) in a biological sample on a substrate. The method includes acquiring, by an image acquisition device, a plurality of images of a first location on the substrate, and classifying, by a processor, objects in the plurality of images into WBC classification groups. The method also includes identifying, by a processor, objects from at least some classification groups, as unclassified objects, and displaying, on a user interface, the unclassified objects and at least some of the classified objects.

The subject disclosure presents systems and methods for automatically selecting meaningful regions on a whole-slide image and performing quality control on the resulting collection of FOVs. Density maps may be generated quantifying the local density of detection results. The heat maps as well as combinations of maps (such as a local sum, ratio, etc.) may be provided as input into an automated FOV selection operation. The selection operation may select regions of each heat map that represent extreme and average representative regions, based on one or more rules. One or more rules may be defined in order to generate the list of candidate FOVs. The rules may generally be formulated such that FOVs chosen for quality control are the ones that require the most scrutiny and will benefit the most from an assessment by an expert observer.

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.

An image segmentation method is disclosed that allows a user to select image component types, for example tissue types and or background, and have the method of the present invention segment the image according to the user's input utilizing the superpixel image feature data and spatial relationships.

Provided is an image processing apparatus configured to process an image of a fundus of an eye, which is capable of simply and accurately measuring a distribution of cells that form a blood vessel wall of an eye. The image processing apparatus includes: an image acquiring unit configured to acquire an image of an eye; a vessel feature acquiring unit configured to acquire membrane candidate points that form an arbitrary wall of a blood vessel based on the acquired image; and a cell identifying unit configured to identify a cell that forms the wall of the blood vessel based on the membrane candidate points.

The purpose of the present invention is to provide a pattern measurement apparatus that appropriately assesses patterns formed by patterning methods for forming patterns that do not exist on photomasks. In order to achieve this purpose, the present invention provides a pattern measurement apparatus comprising a processor that measures the dimensions of patterns formed on a sample by using data acquired by irradiating the sample with a beam, wherein the processor extracts pattern coordinate information on the basis of the data acquired by irradiating the sample with a beam, and uses the coordinate information to generate measurement reference data used when performing dimension measurements of the pattern.

The invention provides a technology for promptly determining bacterial identification or an antimicrobial susceptibility testing. In the invention, first, a state where the bacteria are divided is monitored by performing microscopic observation with respect to the shape or the number of bacteria in each of wells of a culture plate for bacterial identification culture or the antimicrobial susceptibility testing. In addition, the shape, the number or the area of the bacteria are interpreted from the image obtained by the microscopic observation whether or not the bacteria proliferate at a stage from an induction phase to a logarithmic phase, and the time-dependent changes thereof are made into a graph. From the graph, it is determined whether or not the bacteria proliferate for each measurement, the determination results are displayed on the screen, and accordingly, the result of the antimicrobial susceptibility is provided every time when the measurement is performed (FIG. 12).

Provided is an image processing device including a matching unit that performs matching processing between a predetermined pattern on a surface of a 3D model of a biological tissue including an operating site generated on the basis of a preoperative diagnosis image and a predetermined pattern on a surface of the biological tissue included in a captured image during surgery, a shift amount estimation unit that estimates an amount of deformation from a preoperative state of the biological tissue on the basis of a result of the matching processing and information regarding a three-dimensional position of a photographing region which is a region photographed during surgery on the surface of the biological tissue, and a 3D model update unit that updates the 3D model generated before surgery on the basis of the estimated amount of deformation of the biological tissue.