Abstract: A method and apparatus uses multi-material decomposition of three or more material components to generate material-component images from spectral images reconstructed from spectral computed tomography data. In three-component material decomposition e.g., the Mendonça method is used for multi-material decomposition when the attenuation values satisfy an assumed volume fraction condition (i.e., for a given voxel, the attenuation values are within a triangle having vertices given by unit volume fractions of three respective material components). However, when the volume fraction condition fails (e.g., the attenuation values are outside the triangle), either a shortest-Hausdorff-distance method or a closest-edge method is used for multi-material decomposition. For example, the attenuation values of the voxel are projected onto a lower-dimensional space (e.g., the space of a closest edge) and decomposed into a pair/single material component(s) of the lower-dimensional space.

Abstract: A computerized method of providing automatic anatomy recognition (AAR) includes gathering image data from patient image sets, formulating precise definitions of each body region and organ and delineating them following the definitions, building hierarchical fuzzy anatomy models of organs for each body region, recognizing and locating organs in given images by employing the hierarchical models, and delineating the organs following the hierarchy. The method may be applied, for example, to body regions including the thorax, abdomen and neck regions to identify organs.

Abstract: Exemplary methodology, procedure, system, method and computer-accessible medium can be provided for authenticating a non-digital medium of a physical object, by receiving at least one image of video of at least one marked or unmarked region, and comparing the first microscopic image or video of at least one marked or unmarked region with at least one second microscopic image or video relating to the non-digital medium to determine if a similarity between the first and second microscopic images or videos matches or exceeds a predetermined amount.

Abstract: The invention provides an image color enhancement system, method, storage medium and endoscope. Since the human skin color and the basic tone of endoscopic image are similar, a data set of Macbeth color card is utilized to generate a color correction matrix for skin color enhancement. The color correction matrix is used by an endoscope for real time image capture, resulting in a vivid expression of the basic tone of an endoscopic image without introducing artifacts in other tonal image parts.

Abstract: A cross-modality neural network transform for semi-automatic medical image annotation is provided. In various embodiments, an input medical image is mapped to a first vector in a text vector space. The first vector corresponds to the features of the medical image. A set of predetermined vectors is searched for a closest one of the predetermined vectors to the first vector. From the closest one of the predetermined vectors, one or more keywords is determined describing the input medical image.

Abstract: A method of detecting whether or not a body chamber has an abnormal structure or function including: (a) providing a stack of images as input to a system comprising one or more hardware processors configured to obtain a stack of medical images comprising at least a representation of the body chamber inside the patient; to obtain a region of interest using a convolutional network trained to locate the body chamber, wherein the region of interest corresponds to the body chamber from each of the medical images; and to infer a shape of the body chamber using a stacked auto-encoder (AE) network trained to delineate the body chamber, wherein the AE network segments the body chamber; (b) operating the system to detect the body chamber in the images using deep convolutional networks trained to locate the body chamber, to infer a shape of the body chamber using a stacked auto-encoder trained to delineate the body chamber, and to incorporate the inferred shape into a deformable model for segmentation; and (c) detecting

Abstract: An attitude estimation device acquires a plurality of images captured by a plurality of cameras mounted to a vehicle so as to form a plurality of overlap areas in each of which imaging areas partly overlap with each other. The attitude estimation device detects feature portions contained in regions on images respectively including appearances of the overlap areas. Then, the attitude estimation device calculates, for each of the overlap areas, an amount of positional offset between the feature portions detected from the plurality of images respectively including appearances of the overlap areas, and estimates an attitude of the vehicle, based on a difference in the amount of offset calculated for each of the plurality of overlap areas.

Abstract: A method and system for using in a two-modality apparatus. The two-modality apparatus comprises a couch with a table top, a first modality unit and a second modality unit. A second image of a target portion of an object when the table top is at a second working position of the second modality unit may be acquired. A second sag of the table top at a second measurement point of the table top according to the second image may be determined based on the image. A difference between a first sag of the table top at a first measurement point of the table top and the second sag may be estimated based on the second sag and standard data. The standard data provides a relationship relating to a sag of the table top positioned between the first modality unit and second modality unit.

Abstract: A signal processing method is disclosed, which includes detecting a total intensity of X-rays passing through an object comprising multiple materials; obtaining at least one set of basis information of basis material information of the multiple materials and basis component information of photon-electric absorption basis component and Compton scattering basis component of the object; estimating a scatter intensity component of the detected X-rays based on the at least one set of basis information and the detected total intensity; and obtaining an intensity estimate of primary X-rays incident on a detector based on the detected total intensity and the estimated scatter intensity component. An imaging system adopting the above signal processing method is also disclosed.

Abstract: An image processing device (100) includes a change detection unit (101) that detects a target state change in a person on the basis of an input image, and a determination unit (102) that determines an abnormal state in accordance with a detection obtained by detecting occurrences of the target state change in a plurality of persons.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for segmenting a medical image. In one aspect, a method comprises: receiving a medical image that is captured using a medical imaging modality and that depicts a region of tissue in a body; and processing the medical image using a segmentation neural network to generate a segmentation output, wherein the segmentation neural network comprises a sequence of multiple encoder blocks, wherein: each encoder block is a residual neural network block comprising one or more two-dimensional convolutional neural network layers, one or more three-dimensional convolutional neural network layers, or both, and each encoder block is configured to process a respective encoder block input to generate a respective encoder block output wherein a spatial resolution of the encoder block output is lower than a spatial resolution of the encoder block input.

Abstract: The present disclosure provides a method and an apparatus for object re-identification, capable of solving the problem in the related art associated with inefficiency and low accuracy of object re-identification based on multiple frames of images.

Abstract: One example includes a scanning system. The system includes a phase-decorrelation optical coherence tomography (PhD-OCT) scanner configured to implement a scanning sequence via an optical signal on a sample medium. The system also includes a scanning controller configured to provide control signals to the PhD-OCT scanner to implement the scanning sequence and to obtain phase and amplitude information associated with a reflected version of the optical signal. The phase and amplitude information can be indicative of microscale dynamics of the sample medium. The scanning controller can also implement an algorithm to calculate a quantitative parameter of the sample medium based on the phase and amplitude information associated with the sample medium.

Abstract: A computer-implemented method, a computer system, and a computer program product are provided for estimating output data that includes or is based on a number of containers, which may or may not be in receptacles. The method involves using an object detection algorithm operating on an input digital image to detect container images and receptacle images (if any), and using an estimation algorithm operating on the detected images to estimate the number of containers. Estimating the number of containers may involve counting the number of containers within different container classes, as determined by the object detection algorithm. Estimating the number of containers may involve estimating a size of a receptacle in a detected receptacle image based on analysis of a detected reference container image. A detected reference object image may be used to assist with classifying detected container images in different container classes.

Abstract: This disclosure relates to better methods for making garments, for example by capturing images of a subject and making garments for that subject without requiring the subject to visit a tailor for conventional measurement with a tape measure. The disclosed methods provide a faster, easier, and more convenient way to acquire measurements. The disclosed methods also provide better fitting garments and higher customer satisfaction.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining the identity of a user. In one aspect, a method comprises: obtaining at least one image depicting a reflection of light from a lens that is included in a set of eyeglasses; determining, based on the reflection of light from the lens, a set of features characterizing the lens; and determining an identity of a corresponding user based at least in part on the set of features characterizing the lens.

Abstract: A method for performing real-time detection and displaying of polyps in optical colonoscopy, includes a) acquiring and displaying a plurality of real-time images within colon regions to a video stream frame rate, each real-time image comprising a plurality of color channels; b) selecting one single color channel per real-time image for obtaining single color pixels; c) scanning the single color pixels across each the real-time image with a sliding sub-window; d) for each position of the sliding sub-window, extracting a plurality of single color pixels local features of the real-time image; e) passing the extracted single color pixels local features of the real-time image through a classifier to determine if a polyp is present within the sliding sub-window; f) real-time framing on display of colon regions corresponding to positions of the sliding sub-window wherein polyps are detected. A system for carrying out such a method is also provided.

Abstract: A model-based method of inspecting a specimen for presence of one or more interferent, such as Hemolysis, Icterus, and/or Lipemia (HI L) is provided. The method includes generating a pixelated image of the specimen in a first color space, determining color components (e.g., an a-value and a b-value) for pixels in the pixelated image, classifying of the pixels as being either liquid or non-liquid, defining one or more liquid regions based upon the pixels classified as liquid, and determining a presence of one or more interferent within the one or more liquid regions. The liquid classification is based upon a liquid classification model. Pixel classification may be based on a trained multiclass classifier. Interference level for the one or more interferent may be provided. Testing apparatus adapted to carry out the method are described, as are other aspects.

Abstract: Embodiments described herein disclose methods and systems for dynamic object recognition. Using location and information from the recognition process, historical data for a dynamic object, and associated data from secondary objects, a more complete data set can be generated for the dynamic object. The dynamic object data set can then be stored for later recognition and a more complete and human-like understanding of the dynamic object, useful in a variety of automated tasks.

Abstract: In a system and method for analyzing images, an input image is provided to a computer and is processed therein with a first deep learning model so as to generate an output result for the input image; and applying a second deep learning model is applied to the input image to generate an output confidence score that is indicative of the reliability of any output result from the first deep learning model for the input image.