Abstract: An intelligent medical imaging scanner system includes an image scanner, an operator interface, a database, processors, and a storage medium. The database includes a learning model for relating configurations of the image scanner to operator input requirements. The storage medium contains programming instructions that, when executed, cause the processors to determine whether the learning model may be used to generate a configuration of the image scanner corresponding to the new input requirements. If the configuration can be generated, the processors use that configuration to acquire images of a patient using the image scanner. If the configuration of the image scanner cannot be generated, the processors perform an accommodation process comprising (a) modifying the learning model to generate a new configuration of the image scanner corresponding to the new input requirements, and (b) using the new configuration to acquire the images of the patient using the image scanner.

Abstract: A sound source separation method comprising the steps of determining at least one location of at least one sound source based on video data, determining initial estimates of at least two parameters characterizing an audio signal emitted by said sound source, said initial estimates being determined based on said at least one location, performing an expectation-maximization method for determining final estimates of said parameters, and separating the audio signal from a combination of audio signals based on said final estimates of said parameters.

Abstract: An aerial vehicle is navigated using vision-aided navigation that classifies regions of acquired still image frames as featureless or feature-rich, and thereby avoids expending time and computational resources attempting to extract and match false features from the featureless regions. The classification may be performed by computing a texture metric as by testing widths of peaks of the autocorrelation function of a region against a threshold, which may be an adaptive threshold, or by using a model that has been trained using a machine learning method applied to a training dataset comprising training images of featureless regions and feature-rich regions. Such machine learning method can use a support vector machine. The resultant matched feature observations can be data-fused with other sensor data to correct a navigation solution based on GPS and/or IMU data.

Abstract: A method is disclosed for using a camera on-board a vehicle to determine whether precipitation is failing near the vehicle. The method may include obtaining multiple images. Each of the multiple images may be known to photographically depict a “rain” or a “no rain” condition. An artificial neural network may be trained on the multiple images. Later, the artificial neural network may analyze one or more images captured by a first camera secured to a first vehicle. Based on that analysis, the artificial neural network may classify the first vehicle as being in “rain” or “no rain” weather.

Abstract: A medical image reconstruction system and method for correcting a CT image such that the CT image is located at the center of a three-dimensional (3D) space in order to overcome an error that would otherwise be formed due to an inaccurate position of a patient during Obtaining CT images. After the 3D spatial positions of a 3D medical image are corrected using 3D medical image data, a trajectory of a dental arch is detected. A two-dimensional (2D) medical image is created from the 3D medical image through automatic reconstruction on the basis of the detected trajectory of the dental arch.

Abstract: An image recognition apparatus in an embodiment includes a feature-value calculating section configured to calculate a feature value in a region of interest segmented from an image, a likelihood calculating section configured to calculate likelihood of an object present in the region of interest referencing the feature value including a plurality of feature value elements and dictionary data including a plurality of dictionary elements, and a dictionary control section configured to acquire the dictionary element corresponding to the feature value element exceeding a set value.

Abstract: A system (2) including a geometric fit score database (360) configured to store a plurality of 3-D models of faces and a pre-calculated geometric fit score for each of one or more patient interface devices for each of one or more of the faces, and a first processing unit (380) including a match finding unit (382) configured to match the 3-D model of the patient's face with one or more of the stored 3-D models of faces and to use the pre-calculated geometric fit score for each of the one or more of the patient interface devices for the one or more matched faces to determine the geometric fit score for each of the one or more patient interface devices for the patient's face.

Abstract: Automated systems and methods for screening individual plants for increased tolerance or sensitivity to various conditions are provided.

Abstract: A method for determining an incline in a road that is some distance ahead of a motor vehicle relative to the section of road that is currently being driven on by the motor vehicle, wherein images of the road that is ahead of the motor vehicle are recorded by a camera, road path lines are identified ahead of the motor vehicle in the recorded images and the relative incline is calculated with reference to the differences in the courses of the road path lines at different distances.

Abstract: Techniques and systems are provided for processing video data. For example, techniques and systems are provided for matching a plurality of bounding boxes to a plurality of trackers. In some examples, a first association is performed, in which case one or more of the plurality of bounding boxes are associated with one or more of the plurality of trackers by minimizing distances between the one or more bounding boxes and the one or more trackers. A set of unmatched trackers are identified from the plurality of trackers after the first association. The set of unmatched trackers are not associated with a bounding box from the plurality of bounding boxes during the first association. A second association is then performed, in which case each of the set of unmatched trackers is associated with an associated bounding box from the plurality of bounding boxes that is within a first pre-determined distance.

Abstract: A method and system for classifying tissue suspected of being abnormal as being malignant or benign. The method includes generating a set of selection features, performing statistical applications to generate additional selection features, generating a feature vector for the abnormal tissue, feeding the feature vector into a neural network, and obtaining a result from the neural network as to whether the abnormal tissue is malignant or benign. The method and system may be used for determining the presence of breast cancer.

Abstract: Systems and methods for processing a segmented volume from magnetic resonance images that corresponds to a nerve are provided. The segmented volume can be processed to generate a report that provides complementary information on the state or condition of tissues contained in the segmented nerve volume. For example, the segmented volume can be processed to identify regions of suspected inflammation, or other pathology such as demyelination, of the nerve tissue contained in the segmented volume. The systems and methods described here provide a user-defined approach to identifying regions of suspected inflammation, or other pathology, in a segmented nerve volume.

Abstract: The present disclosure provides a system and method for CT image reconstruction. The method may include combining an analytic image reconstruction technique with an iterative reconstruction algorithm of CT images. The image reconstruction may be performed on or near a region of interest.

Abstract: Vision-assist systems including user eye tracking cameras are disclosed. A vision-assist system includes a processor, a memory module communicatively coupled to the processor, a user eye tracking camera communicatively coupled to the processor, an environment camera communicatively coupled to the processor, a feedback device communicatively coupled to the processor, and machine readable instructions stored in the memory module that, when executed by the processor, cause the vision-assist system to receive environment image data from the environment camera, determine a location of an individual speaking to a user based on the environment image data, receive user eye tracking image data from the user eye tracking camera, determine a pose of the user's eyes based on the user eye tracking image data, and provide feedback to the user with the feedback device based on the location of the individual speaking to the user and the pose of the user's eyes.

Abstract: A system and method for calculating step count and associated physical movement intensity. In some embodiments, the system includes at least a camera to capture video of user motions, which are analyzed, and the corresponding step count and physical exercise intensity are deduced by the disclosed method.

Abstract: Disclosed are systems, devices, and methods for detecting a trachea, an exemplary system comprising an imaging device configured to obtain image data and a computing device configured to generate a three-dimensional (3D) model, identify a potential connected component in a first slice image, identify a potential connected component in a second slice image, label the first slice image as a top slice image, label the connected component in the top slice image as an active object, associate each connected component in a current slice image with a corresponding connected component in a previous slice image based on a connectivity criterion, label each connected component in the current slice image associated with a connected component of the preceding slice image as the active object, and identify the active object as the trachea, based on a length of the active object.

Abstract: A plant growth measurement and prediction system uses drone-captured images to measure the current growth of particular plant species and/or to predict future growth of the plant species. For example, the system instructs a drone to fly along a flight path and capture images of the land below. The captured images may include both thermographic images and high-resolution images. The system processes the images to create an orthomosaic image of the land, where each pixel in the orthomosaic image is associated with a brightness temperature. The system then uses plant species to brightness temperature mappings and the orthomosaic image to identify current plant growth. The system generates a diagnostic model using the orthomosaic image to then predict future plant growth.

Abstract: Devices and systems for image-based analysis of test media are disclosed herein. An example device includes four side panels connected together so as to form a tubular rectangle, a floor panel that covers an opening of the tubular rectangle, the floor panel having a raised test bed that receives a test medium, a top panel that having an optical lens that aligns with the raised test bed when the top panel covers another opening of the tubular rectangle. The optical lens is aligned with an aperture that extends through the top panel. The four side panels, the floor panel, and the top panel forming an optic chamber when joined together. The device also includes a light source that illuminates inside the device.

Abstract: Content is identified using watermarking and/or other content recognition combined with contextual metadata, which facilitates identification and correlation with other content and metadata when it is posted to a network.

Abstract: Systems and methods for image guidance, which may include an image processing unit, cameras, and handheld real-time imaging components or handheld displays, wherein the cameras observe visual features on patients, tools, or other components, and wherein said features allow camera or object positions to be determined relative to secondary image data or a reference position, and wherein the image processing unit is configured to dynamically register observations with secondary image data, and to compute enhanced images based on combinations of one or more of secondary image data, positioning data, and real-time imaging data.