Abstract: Embodiments for registering features in a repeating pattern are described. These embodiments can include providing an object having a repeating pattern of features and a fiducial. These embodiment can also include obtaining a target image of the object, where the target image includes the repeating pattern of features and the fiducial. These embodiment can also include comparing the fiducial in the target image to reference data, where the reference data includes xy coordinates for a virtual fiducial. These embodiment can also include determining locations for the features in the target image based on the comparison of the virtual fiducial in the reference data to the fiducial in the data from the target image. The fiducial can have at least concentric circles that produce three different signal levels. The locations of the features can be determined at a variance of less than 5 ?m.

Abstract: Systems and methods are disclosed for automatically segmenting a heart chamber from medical images of a patient. The system may include one or more hardware processors configured to: obtain image data including at least a representation of the patient's heart; obtain a region of interest from the image data; organize the region of interest into an input vector; apply the input vector through a trained graph; obtain an output vector representing a refined region of interest corresponding to the heart based on the application of the input vector through the trained graph; apply a deformable model on the obtained output vector representing the refined region of interest; and identify a segment of a heart chamber from the application of the deformable model on the obtained output vector.

Abstract: A method for analyzing an image of a lesion on the skin of a subject including (a) identifying the lesion in the image by differentiating the lesion from the skin; (b) segmenting the image; and (c) selecting a feature of the image and comparing the selected feature to a library of predetermined parameters of the feature. The feature of the lesion belongs to any one selected from the group: color, border, asymmetry and texture of the image.

Abstract: An image processing apparatus includes an image input that receives input of image data of a captured human being, a region detector that detects a specific color region of the image data, a filter that smooths a pixel value in the specific color region detected by the region detector by using a frame of the image data input into the image input and each of previous and subsequent frames of the image data of the inputting into the image input, a coder that codes an output image of the filter, and an output that outputs the output image of the filter coded by the coder.

Abstract: An X-ray computed tomography (CT) apparatus according to an embodiment includes processing circuitry. The processing circuitry causes a CT image designated as a display object image to be displayed on a display, every time any of a plurality of reconstructed CT images is designated as the display object image. The processing circuitry causes a newly reconstructed enlarged CT image to be displayed on the display when the processing circuitry receives an enlargement instruction to enlarge the CT image displayed on the display. The processing circuitry performs preprocessing on raw data corresponding to the CT image designated as the display object image, every time any of the CT images is designated as the display object image. The processing circuitry reconstructs the enlarged CT image using the preprocessed raw data, based on the enlargement instruction, when the processing circuitry receives the enlargement instruction.

Abstract: Methods and apparatus for displaying information from a three dimensional imaging data cube, having particular application in ophthalmology, are disclosed. The method of the present invention slices 3D imaging data along curved surfaces that match anatomical layers, and comprising four steps: a locating step in which anatomical layers are located; a selecting step in which a slicing surface is selected based on the locations of the anatomical layers; an extracting step, wherein the user extracts data values that fall on the slicing surface selected; and a displaying step in which the data values extracted are displayed as a three dimensional image. The apparatus of the subject invention comprises hardware and software that employ the method of the subject invention to display improved anatomical 3D images.

Abstract: An apparatus comprises processing circuitry configured to: obtain medical imaging data that is representative of an anatomical region of a subject, the anatomical region comprising at least one anatomical feature of interest; obtain a template that is representative of a desired view of the at least one anatomical feature of interest; register the medical imaging data and reference anatomical data to obtain a distribution of registration probability with respect to at least one registration parameter; and perform a selection process comprising: obtaining a plurality of transforms, each having an associated registration; for each of the plurality of transforms: generating a respective view of the at least one anatomical feature of interest based on said transform; and determining a template matching probability that represents a similarity of the generated view to the template; and selecting at least one of the transforms and/or at least one of the views based on a combination of at least one of the registrati

Abstract: A first instance of a digital watermark may be embedded into an image. The first instance may encode information. A second instance of the digital watermark may be embedded into the image. The second instance may encode the information of the first instance. The second instance may be a sized differently or may be larger than the first instance.

Abstract: Disclosed herein are methods for analyzing cell kinematics in a nucleated cell culture from a time-series sequence of multiple fluorescence microscopic images of the nucleated cell culture. The method includes the steps of, (a) identifying every cell nucleus in each fluorescence microscopic image; (b) identifying every cell cluster using the cell nuclei identified in the step (a); and (c) tracking the cells and/or cell clusters using the cell nuclei and cell clusters identified for the fluorescence microscopic images in steps (a) and (b) respectively.

Abstract: A method is for determining a respiratory phase is based on receiving tomographic raw data on the basis of a spiral scan of an examination region of a patient, the examination region including at least part of the torso and/or abdomen of the patient. Slice image pairs are reconstructed on the basis of the tomographic raw data, wherein a slice image pair includes two slice images having a first interval at an identical position along a predefined axis. The position refers to the position of the examination region. This enables determining of differences between reference positions of the examination region in two slice images respectively of a slice image pair and determining a respiratory phase on the basis of the differences. The differences correspond in each case to the change in the anatomy of the examination region, wherein this change occurs during the first interval.

Abstract: A method includes: sensing a portion of a human body to generate a series of image frames by an optical sensing element; determining a complexion region from each of the image frames; then calculating a central coordinate of the complexion region; determining a sample block by expanding a surrounding range from the central coordinate, for getting a complexion fluctuation waveform; comparing the central coordinate with a central coordinate of a later image frame, to calculate a displacement in a unit time for determining whether the portion of the human body is in a static state. In the static state, an operating unit performs noise filter and peak detecting for complexion fluctuation waveform, and calculates a physiological signal. The method can reduce the amount of data required to be processed in physiological signal detection, and improve the accuracy of the detection.

Abstract: Method and apparatus are used to display a slice of tomographic image in a three-dimensional (3D) medical image, for the purpose of achieving better recognition of a vascular structure contained in the slice without degrading spatial resolution of the slice. An example method includes identifying a slice of interest in a 3D medical image representing an anatomical part including a blood vessel; and projecting along a slice axis direction orthogonal to the slice of interest for a region in the 3D medical image including the slice and wider than the slice.

Abstract: Technology is disclosed for inferring human attributes from images of people. The attributes can include, for example, gender, age, hair, and/or clothing. The technology uses part-based models, e.g., Poselets, to locate multiple normalized part patches from an image. The normalized part patches are provided into trained convolutional neural networks to generate feature data. Each convolution neural network applies multiple stages of convolution operations to one part patch to generate a set of fully connected feature data. The feature data for all part patches are concatenated and then provided into multiple trained classifiers (e.g., linear support vector machines) to predict attributes of the image.

Abstract: A system for and method for improved computer vision image processing and image segmentation and recognition is disclosed. The system and method utilizes a cost function approach for improved image segmentation and recognition. In particular, a global cost function is defined and then the global cost function is minimized. This global cost function takes into account two processing pipelines of data determined by the operation of two different processing technologies upon the target input image. Constraints are utilized to ensure data consistency across the model and between the data pipelines. The system and method are useful for processing low quality images containing alphanumeric data such as floorplan images.

Abstract: Systems and methods for dynamic anti-glare for a windshield of a vehicle. One embodiment is a system that includes a camera to capture image data of an environment in front of the vehicle, a projector to display an image on the windshield, and a sensor to monitor light intensity for an area of the windshield. The system also includes a controller that, in response to detecting glare impinging on the area of the windshield via the sensor, analyzes the image data captured for the area of the windshield, determines a location of the glare in the area based on the image data, determines a characteristic of the environment for the area based on the image data, generates a counteracting image based on the characteristic of the environment for the area, and directs the projector to display the counteracting image on the location of the windshield to reduce the glare.

Abstract: The invention relates to an image generation apparatus (1) for generating an image of an object. A reconstruction unit (10) reconstructs the image based on provided measured projection values such that costs defined by a cost function are reduced, wherein the cost function depends on differences between calculated projection values, which have been determined by simulating a forward projection through the image, and the provided measured projection values, and wherein a degree of dependence of the cost function on a respective difference depends on the respective difference. This can allow for a consideration of a degree of disturbance of the measured projection values by motion and/or by an incomplete illumination of the object during the reconstruction process, which can lead to a reconstruction of an image having an improved image quality.

Abstract: A method for edge determination of a measurement object in optical metrology, such as performed by an optical coordinate measuring machine. The method includes the steps of capturing first image data of the measurement object under reflected-light illumination, capturing second image data of the measurement object under transmitted-light illumination, and determining a position of an edge of the measurement object based on an evaluation in which both the first and the second image data are used.

Abstract: A method for extracting a blood vessel is provided. An image relating to a blood vessel may be acquired. The image may include multiple slices. A region of interest in the image may be determined. A blood vessel model may be obtained. The blood vessel may be extracted from the region of interest based on the blood vessel model.

Abstract: Presented are techniques for processing medical images. The techniques can include accessing a stored medical image and electronically representing a plurality of overlapping tiles that cover the medical image, each overlapping tile including a non-overlapping inner portion and an overlapping marginal portion. The techniques can also include in parallel, and individually for each of a plurality of the overlapping tiles: applying a segmentation process to identify objects in the at least one medical image, identifying inner object data representing at least one inner object that is contained within an inner portion of at least one tile, and identifying marginal object data representing at least one marginal object that overlaps a marginal portion of at least one tile. The techniques can also include merging at least some of the marginal object data to produce merged data, and outputting object data including the inner object data and the merged data.

Abstract: Embodiments are directed to classifying barcode tag conditions on sample tubes from top view images to streamline sample tube handling in advanced clinical laboratory automation systems. The classification of barcode tag conditions leads to the automatic detection of problematic barcode tags, allowing for a user to take necessary steps to fix the problematic barcode tags. A vision system is utilized to perform the automatic classification of barcode tag conditions on sample tubes from top view images. The classification of barcode tag conditions on sample tubes from top view images is based on the following factors: (1) a region-of-interest (ROI) extraction and rectification method based on sample tube detection; (2) a barcode tag condition classification method based on holistic features uniformly sampled from the rectified ROI; and (3) a problematic barcode tag area localization method based on pixel-based feature extraction.