Abstract: A method includes obtaining a first imaging scan and a second imaging scan of a single subject brain. The first imaging scan is converted to a first dataset, and the second imaging scan is converted to a second dataset. A sequence-adaptive multimodal segmentation algorithm is applied to the first dataset and the second dataset. The sequence-adaptive multimodal segmentation algorithm performs automatic intensity-based tissue classification to generate a first labelled dataset and a second labeled dataset. The first labeled dataset and the second labeled dataset are automatically co-registered to each other to generate a transformation matrix based on the first labeled dataset and the second labeled dataset. The transformation matrix is applied to align the first dataset and the second dataset.

Abstract: A network-connected security device is communicatively coupled to an audio/video (A/V) recording and communication device having a camera and a speaker. A method receives video data captured by the camera, and performs an object recognition algorithm upon the received video data to identify an object therein. The method performs a table lookup using the identified object, into a data structure that associates objects with at least one description of a predefined voice message. The method selects a description of a predefined voice message associated with the identified object, and transmits the selected description's predefined voice message to the A/V recording and communication device for output through the speaker.

Abstract: To make it possible to set a parameter, which is used for detection of a mark attached to a ground marker, according to the feature of the mark. Provided is an information processing apparatus including: an acquisition unit that acquires a captured image; a detection unit that detects a feature of a target object in the captured image; and a determination unit that determines, on the basis of the feature, a parameter used for an assessment of whether or not the target object is a predetermined object.

Abstract: Various example embodiments of the present disclosure provide systems and methods for performing image-guided navigation during medical procedures using intraoperative surface detection. A surface detection device is employed to obtain intraoperative surface data characterizing multiple surface regions of a subject. Pre-operative volumetric image data is registered to each surface region, providing per-surface-region registration transforms. In some example embodiments, navigation images may be generated intraoperatively based on the dynamic selection of a suitable registration transform. For example, a registration transform for generating navigation images may be dynamically determined based on the proximity of a tracked surgical tool relative to the surface regions. In an alternative example embodiment, multiple navigation images may be displayed, wherein each navigation image is generated using a different registration transform.

Abstract: Systems and methods for improving soft tissue contrast, characterizing tissue, classifying phenotype, stratifying risk, and performing multi-scale modeling aided by multiple energy or contrast excitation and evaluation are provided. The systems and methods can include single and multi-phase acquisitions and broad and local spectrum imaging to assess atherosclerotic plaque tissues in the vessel wall and perivascular space.

Abstract: Provided are methods for deep learning-based camera calibration, which can include receiving first and second images captured by a camera, processing the first image using a first neural network to determine a depth of the first image, processing the first image and the second image using a second neural network to determine a transformation between a pose of the camera for the first image and a pose of the camera for the second image, generating a projection image based on the depth of the first image, the transformation of the pose of the camera, and intrinsic parameters of the camera, comparing the second image and the projection image to determine a reprojection error, and adjusting at least one of the intrinsic parameters of the camera based on the reprojection error. Systems and computer program products are also provided.

Abstract: An apparatus that calibrates a parametric mapping that maps between object points and image points. The apparatus captures an image of a calibration pattern including features defining object points. The apparatus determines, from the image, measured image points that correspond to the object points. The apparatus determines, from the mapping, putative image points that correspond to the object points. The apparatus minimizes a cumulative cost function dependent upon differences between the measured image points and putative image points to determine parameters of the parametric mapping. The mapping uses a parametric function to specify points where light rays travelling from object points to image points cross the optical axis.

Abstract: The present disclosure relates to systems and methods for characterizing a behavior change of a process. A behavior model that can include a set of behavior parameters can be generated based on behavior data characterizing a prior behavior change of a process. A stimulus parameter for a performance test can be determined based on the set of behavior parameters. An application of the performance test to the process can be controlled based on the stimulus parameter to provide a measure of behavior change of the process. Response data characterizing one or more responses associated with the process during the performance test can be received. The set of behavior parameters can be updated based on the response data to update the behavior model characterizing the behavior change of the process. In some examples, the behavior model can be evaluated to improve or affect a future behavior performance of the process.

Abstract: A computer-implemented method executed by at least one processor for reducing radial distortion errors in fish-eye images is presented. The method includes capturing an image from a camera including distortions, detecting arc-shaped edge segments in the image including the distortions, estimating a main distortion parameter by fixing a distortion centerpoint in a middle of the image, estimating the distortion centerpoint with the main distortion parameter, and obtaining an undistorted version of the captured image by inverting the distortion model.

Abstract: A method of treating a human patient identified as having an injury to a body region includes receiving CT images, where the CT images were generated by performing a CT angiography of an injured body region of the human patient. The method further includes determining, based on the CT images, a total volumetric rate of active bleeding in the injured body region; and recommending at least one treatment approach for the human patient based on the total volumetric rate of active bleeding.

Abstract: A method of orthodontic treatment planning for a patient includes receiving three-dimensional intraoral surface scan data of a dentition of the patient, receiving three-dimensional volumetric scan data of the dentition of the patient, and overlaying the intraoral surface scan data and the volumetric scan data to generate an integrated patient model comprising a root of at least one tooth having a longitudinal axis. The method further includes determining, for use in planning an orthodontic treatment, a center of rotation of the at least one tooth, wherein the center of rotation is defined as a point located a predetermined distance from a base of the root to an apex of the root along the longitudinal axis of the at least one tooth in the integrated patient model.

Abstract: The present invention is related to improved methods for analysis of images of the vitreous and/or retina and/or choroid obtained by optical coherence tomography and to methods for making diagnoses of retinal disease based on the reflectivity profiles of various vitreous and/or retinal and/or choroidal layers of the retina.

Abstract: Systems and methods for property feature detection and extraction using digital images. The image sources could include aerial imagery, satellite imagery, ground-based imagery, imagery taken from unmanned aerial vehicles (UAVs), mobile device imagery, etc. The detected geometric property features could include tree canopy, pools and other bodies of water, concrete flatwork, landscaping classifications (gravel, grass, concrete, asphalt, etc.), trampolines, property structural features (structures, buildings, pergolas, gazebos, terraces, retaining walls, and fences), and sports courts. The system can automatically extract these features from images and can then project them into world coordinates relative to a known surface in world coordinates (e.g., from a digital terrain model).

Abstract: An array (map) of intrinsic images of an image of interest is established by selecting the intensities of a focused and defocused/diffused images of the image of interest. After obtaining a first focused image, a series of defocused/diffused images are obtained at different exposure times, where intrinsic images are obtained from the first focused image and the series of defocused/diffused images in order to form an array of image sets of the intrinsic images in the form of a matrix. In addition, a second focused image can be obtained at a different exposure time than the first focused image, and a second series defocused/diffused images are obtained at different exposure times, where second intrinsic images are obtained from the second focused image and the second series of defocused/diffused images in order to form an array of image sets of the intrinsic images and the second intrinsic images in the form of a matrix.

Abstract: Systems and methods are described herein for tracking an elongate instrument or other medical instrument in an image.

Abstract: Systems for detecting and measuring certain dental defects and/or existing restorations, such as lesions which may or may not invade interproximal areas, using a neural network is disclosed. In some embodiments, a patient's health conditions and certain dental conditions such as crowding, presence of implants, gum disease, etc. are also considered by an automated system to classify the dental health of a patient into one or more risk classes. The system then suggests appropriate remedial measures and an appropriate maintenance program for that patient to keep therapy within guidelines of proven standard of care, leading the way to reduce tooth loss in population.

Abstract: A system for updating continuous image alignment of separate cameras identifies a previous alignment matrix associated with a previous frame pair captured at one or more previous timepoints by a reference camera and a match camera. The previous alignment matrix is based on visual correspondences in the previous frame pair. The system also identifies a current matrix associated with a current frame pair captured at one or more current timepoints by the reference camera and the match camera. The current matrix is based on visual correspondences in the current frame pair. The system also identifies a difference value associated with the reference camera or the match camera relative to the one or more previous timepoints and the one or more current timepoints. The system also generates an updated alignment matrix by using the previous alignment matrix, the current matrix, and the difference value as inputs.

Abstract: A method for acquiring a distance from a moving body to an object located in any direction of the moving body includes steps of: an image processing device (a) instructing a rounded cuboid sweep network to project pixels of images, generated by cameras covering all directions of the moving body, onto N virtual rounded cuboids to generate rounded cuboid images and apply 3D concatenation operation thereon to generate an initial 4D cost volume, (b) instructing a cost volume computation network to generate a final 3D cost volume from the initial 4D cost volume, and (c) generating inverse radius indices, corresponding to inverse radii representing inverse values of separation distances of the N virtual rounded cuboids, by referring to the final 3D cost volume and extracting the inverse radii by using the inverse radius indices, to acquire the separation distances and thus, the distance from the moving body to the object.

Abstract: Apparatus for determining a spatial property in a 3D-space, wherein the apparatus comprises a physical pointer, a camera and a position and orientation measurement system, wherein a first object in the 3D-space comprises a pattern on it, wherein the physical pointer is configured to contact a surface area of a second object in the 3D-space, wherein the camera is configured to capture, at a position of the camera with respect to the first object, image data comprising an image of the pattern; wherein the position and orientation measurement system is configured to determine a heading, position, verticality, attitude, and/or inclination of the camera based on the image of the pattern, and determine, based on the determined heading, position, verticality, attitude, and/or inclination of the camera and a relative position of the physical pointer with respect to the camera, the spatial property of the surface area by the physical pointer.

Abstract: A method is disclosed including: receiving raw image data corresponding to a series of raw images; processing the raw image data with an encoder to generate encoded data, where the encoder is characterized by an input/output transformation that substantially mimics the input/output transformation of one or more retinal cells of a vertebrate retina; and applying a first machine vision algorithm to data generated based at least in part on the encoded data.