Abstract: An approach is provided for rendering a distance marker in an image. The approach, for example, involves determining a plurality of camera characteristics of a camera used to capture the image. The plurality of camera characteristics, for instance, can include a camera field of view, a horizon offset, a camera mounting height, a camera mounting axis, or a combination thereof. The approach also involves determining a ground plane extending to a horizon depicted in the image, a camera position with respect to the ground plane, and an image plane based on the plurality of characteristics, wherein the image plane is orthogonal to the ground plane and intersects the ground plane at a designated distance from the camera position. The approach further involves projecting a ray from the camera position through the distance marker on the ground plane to a marker position on the image plane, and rendering the distance marker in the image based on the marker position on the image plane.

Abstract: A method for providing a singling device of a storage and dispensing container for drug portions is provided. A singling device is adapted to a specific drug portion based on the measurement of the drug portion. The measurement is obtained by generating at least one image of a to-be-measured drug portion by a detection device and using image analysis to process the at least one image. Drug information for the specific drug portion is determined, the drug information including at least the dimensions of the specific drug portion. Based on the determined drug information, a singling device fitting the drug portion to be singularized is identified and provided for use in the storage and dispensing container. A system for identifying a singling device is also provided.

Abstract: Medical software tools platforms utilize a surgical display to provide access to specific medical software tools, such as medically-oriented applications or widgets, that can assist surgeons or surgical team in performing various procedures. In particular, an endoscopic camera may register the momentary rise in the optical signature reflected from a tissue surface and in turn transmit it to a medical image processing system which can also receive patient heart rate data and display relevant anomalies. Changes in various spectral components and the speed at which they change in relation to a source of stimulus (heartbeat, breathing, light source modulation, etc.) may indicate the arrival of blood, contrast agents or oxygen absorption. Combinations of these may indicate various states of differing disease or margins of tumors, and so forth. Also, changes in temperatures, physical dimensions, pressures, photoacoustic pressures and the rate of change may indicate tissue anomalies in comparison to historic values.

Abstract: Provided is a method for CT image denoising based on deep learning, and the method for CT image denoising based on deep learning includes: extracting examination information from an input CT image; selecting at least one deep learning model corresponding to the examination information from multiple previously trained deep learning models; and outputting a CT image denoised from the input CT image by feeding the input CT image into the selected at least one deep learning model.

Abstract: Systems and methods for intraocular lens selection include receiving, by one or more computing devices implementing a prediction engine, pre-operative multi-dimensional images of an eye; extracting, by the prediction engine, pre-operative measurements of the eye based on the pre-operative images; estimating, by the prediction engine using a prediction model based on a machine learning strategy, a post-operative position of an intraocular lens based on the extracted pre-operative measurements; selecting a power of the intraocular lens based on the estimated post-operative position of the intraocular lens; and selecting the intraocular lens based on the selected power. In some embodiments, the systems and methods further include receiving post-operative multi-dimensional images of the eye after implantation of the selected intraocular lens, extracting post-operative measurements of the eye, and updating the prediction model based on the pre-operative measurements and the post-operative measurements.

Abstract: Described herein is a method of detecting anomalies on a surface of a structure. The method may comprise taking a thermal image of the surface of the structure. The method may further comprise taking a visual image of the surface of the structure. The method may then comprise conducting a thermal image numerical analysis on the thermal image. The thermal image numerical analysis may comprise obtaining a thermal image numerical value table. The thermal image numerical analysis may then comprise obtaining a surface nominal thermal value of the surface material. The thermal image numerical analysis may then comprise eliminating a first subset of pixels having a thermal value within a nominal thermal variation from the plurality of pixels. The thermal image numerical analysis may then comprise comparing the thermal value of each pixel of the plurality of pixels not in the first subset of pixels to the surface nominal thermal value to identify at least one anomaly.

Abstract: Provided is an object detection device for efficiently and simply selecting an image for creating instructor data on the basis of the number of detected objects. The object detection device is provided with: a detection unit for detecting an object from each of a plurality of input images using a dictionary; an acceptance unit for displaying, on a display device, a graph indicating the relationship between the input images and the number of subregions in which the objects are detected, and displaying, on the display device, in order to create instructor data, one input image among the plurality of input images in accordance with a position on the graph accepted by operation of an input device; a generation unit for generating the instructor data from the input image; and a learning unit for learning a dictionary from the instructor data.

Abstract: A method, a system, and a computer program product for visually identifying the at least one target subject within a real-time view of a current scene. The method includes capturing, by at least one image sensor, a real-time view of a current scene. The method further includes performing a visual analysis of the real-time view to identify at least one subject. The method further includes: receiving, in real-time, a natural language input which includes verbal utterances of at least one speaker; and identifying, within the natural language input, a description of at least one particular subject. The method further includes: analyzing the current scene to identify at least one target subject that matches the description of the at least one particular subject; and in response to identifying the at least one target subject, applying at least one visual identifier to the real-time view of the current scene.

Abstract: At least one processor of a computing device may determine relevancy metadata associated with of images stored in an imagery processing system. The at least one processor may determine one or more active retention policies for the images based at least in part on the relevancy metadata, wherein the one or more active retention policies include one or more rulesets that are applied to the relevancy metadata. The at least one processor may determine retention priority values associated with the images stored in the imagery processing system based at least in part on the one or more active retention policies. The at least one processor may manage retention of the images in the imagery processing system based at least in part on the retention priority values associated with the images.

Abstract: Systems, and method and computer readable media that store instructions for scale invariant object detection.

Abstract: The following concerns a method for co-localization of microscopy or histology stains by the assembly of a virtual image from one or more imaging operations. In particular, the method decreases the time required to obtain multiple labeled antigen or protein histology images of a biological sample. The method includes imaging the tissue as it is sliced by a microtome with a knife edge scanning microscope and spatially aligning the samples by the generated images. The spatial alignment of samples enabled by the method allows a panel of different antigen or protein secondary or functional stains to be compared across different sample slices, thereby allowing concurrent secondary stains of tissues and cells.

Abstract: A vehicle camera device is suitable to be provided in a first vehicle. The vehicle camera device receives at least one of a vehicle speed value of the first vehicle, a distance value between the first vehicle and a second vehicle, and an afterimage motion amount of an image of the second vehicle, and selects one of a plurality of exposure parameter functions according to at least one of the vehicle speed value of the first vehicle, the distance value and the afterimage motion amount to determine an optimized parameter value.

Abstract: Poses or gestures of actors within a scene may be detected and tracked using multiple imaging devices aligned with fields of view that overlap at least in part. Images captured by the imaging devices may be synchronized and provided to a classifier to recognize body parts within the images, and score maps indicative of locations of peak probabilities that the images include the respective body parts may be generated. Locations of peak values within the score maps may be correlated with one another to confirm that a given body part is depicted in two or more fields of view, and vectors indicative of distances to or ranges of motion of body parts, with respect to the given body part, may be generated. Motion of the body parts may be tracked in subsequent images, and a virtual model of the body parts may be generated and updated based on the motion.

Abstract: A method for character recognition and semantic for natural language processing comprising extracting a sequence of feature vectors from a sequence of input character images by a convolutional neural network (CNN) feature extractor. The sequence of feature vectors comprises a plurality of feature vectors, each feature vector representing an approximate-match of its corresponding input character in the sequence of input character images. The method further comprises applying a sequential classifier sequentially as a sliding window of a size of a plurality consecutive feature vectors upon the sequence of feature vectors from a first feature vector in the sequence of feature vectors to the last feature vector in the sequence of feature vectors; and recognizing an output character for a targeted feature vector among the applied-upon consecutive feature vectors within the sliding window as it is sliding across the sequence of feature vectors.

Abstract: Image analysis techniques may be employed to identify moving and/or static object within a sequence of spatial data frames (102, 300). Attributes of interest may be identified within a sequence of spatial data frames (102, 300). The attributes of interest may be clustered and examined across frames of the spatial data to detect motion vectors. A system (200) may derive information about these attributes of interest and their motion over time and identify moving and/or static objects, and the moving and/or static objects may be used to generate natural language messages describing the motion of the attributes of interest. Example uses include description of moving and/or static objects in data such as weather data, oil spills, cellular growth (e.g., tumor progression), atmospheric conditions (e.g., the size of a hole in the ozone layer), or any other implementation where it may be desirable to detect motion vectors in a sequence of spatial data frames.

Abstract: A designation device includes a storage that stores therein a three-dimensional model of an organ, and a processor coupled to the storage. The processor executes a process including: first acquiring designations of a plurality of planes of the three-dimensional model of the organ; second acquiring designations of a specific number of pieces of point information indicating an infarct site of the organ for any one or all of the planes; determining the infarct site of the organ that is interposed between the planes on the basis of the pieces of point information; and outputting an image reproducing determination result of the infarct site of the organ at the determining using the three-dimensional model.

Abstract: In an energy subtraction processing apparatus, method, and a non-transitory computer readable recording medium storing program, a high-quality image is generated by acquiring an absorption coefficient suitable for a subject. A subject information acquisition unit acquires the thickness information of a breast and a mammary gland content rate, as subject information, based on a low voltage image acquired by energy subtraction imaging. An absorption coefficient acquisition unit acquires an absorption coefficient corresponding to the subject information with reference to the relationship between the thickness of the breast and the X-ray absorption coefficient, which is calculated in advance. Based on the absorption coefficient acquired by the absorption coefficient acquisition unit, a weighting coefficient calculation unit calculates a weighting coefficient at the time of performing energy subtraction processing.

Abstract: A method and system for registration of a multi-dimensional image include defining an input image and a reference image in the same fixed Cartesian grid, then mapping locations within the reference image and the input image to phase space using a Hamiltonian function to define a symplectomorphic map, where the map is embedded in an energy shell. The mapping step is iterated until a sequence of energy shells is created. The energy shells are used generate curvilinear mapping grid which is then applied to the first image to generate a registered output image data. The data may be preconditioned to account for nearest neighbor coupling and/or to equalize the dimensionality of the images.

Abstract: Methods, systems, and storage media for image thresholding at a network edge device are disclosed herein. In an embodiment, a network edge device may include a camera to be operated by at least one of the one or more processors to capture a monitoring image of a condition proximal to the device at a location. An image threshold module may be operated by at least one of the one or more processors to determine if the monitoring image exceeds a threshold relating to the condition at the location. A communication module may communicate to a remote network location an indication if the monitoring image exceeds the threshold relating to the condition.

Abstract: A computer implemented method of generating at least one shape of a region of interest in a digital image is provided.