Abstract: A system for computational localization of fibrillation sources is provided. In some implementations, the system performs operations comprising generating a representation of electrical activation of a patient's heart and comparing, based on correlation, the generated representation against one or more stored representations of hearts to identify at least one matched representation of a heart. The operations can further comprise generating, based on the at least one matched representation, a computational model for the patient's heart, wherein the computational model includes an illustration of one or more fibrillation sources in the patient's heart. Additionally, the operations can comprise displaying, via a user interface, at least a portion of the computational model. Related systems, methods, and articles of manufacture are also described.

Abstract: Systems and methods are disclosed to objectively identify sub-second behavioral modules in the three-dimensional (3D) video data that represents the motion of a subject. Defining behavioral modules based upon structure in the 3D video data itself—rather than using a priori definitions for what should constitute a measurable unit of action—identifies a previously-unexplored sub-second regularity that defines a timescale upon which behavior is organized, yields important information about the components and structure of behavior, offers insight into the nature of behavioral change in the subject, and enables objective discovery of subtle alterations in patterned action. The systems and methods of the invention can be applied to drug or gene therapy classification, drug or gene therapy screening, disease study including early detection of the onset of a disease, toxicology research, side-effect study, learning and memory process study, anxiety study, and analysis in consumer behavior.

Abstract: Embodiments provide the capability to determine a digital 3D model of a patient's teeth obtains projection images acquired by scanning a negative impression of the patient's teeth using a computed tomographic imaging apparatus, where the impression includes a radio-opaque transfer element for a dental implant or crown post. One exemplary method reconstructs, from the projection images, an air volume model within the reconstructed volume and bounded by a transition surface defined according to the negative impression. A transfer element volume model of the transfer element is defined, segmented from the air volume model and from the transition surface. A combined digital 3D model of the patient's teeth is formed according to the air volume model and transfer element volume model. At least a portion of the combined digital 3D model of the teeth is displayed.

Abstract: Systems, devices, media, and methods are presented for segmenting an image of a video stream with a client device, identifying an area of interest, generating a modified area of interest within one or more image, identifying a first set of pixels and a second set of pixels, and modifying a color value for the first set of pixels.

Abstract: Various methods and systems for improved anterior segment optical coherence tomography (OCT) imaging are described. One example method includes collecting a set of B-scans over a range of different transverse locations on the cornea, segmenting each B-scan to identify an anterior corneal layer and an outer edge of Bowman's layer, calculating thickness values for each B-scan by computing the distance from the anterior corneal layer to the outer edge of the Bowman's layer, combining the thickness values from the B-scans to create a polar epithelial thickness map, converting the polar epithelial thickness map to a Cartesian epithelial thickness map using a fitting method, and storing or displaying the Cartesian epithelial thickness map or information derived from the Cartesian epithelial thickness map.

Abstract: Systems and methods for determining an ROI of a subject are provided. In some embodiments, the system may obtain a target image including the subject situated on a table. The system may also obtain a focus position associated with the ROI of the subject to be scanned or treated by a medical device in the target image. The system may further determine a target table position based on the focus position. In some embodiments, the system may obtain a model image corresponding to the subject. The system may also obtain a virtual area corresponding to a virtual ROI in the model image. The system may also obtain a positioning image of the subject. The system may further determine, in the positioning image, a target area corresponding to the ROI of the subject corresponding to the virtual ROI based on the virtual area and the positioning image.

Abstract: Techniques for managing secure login with authentication while viewing a unique code are described. In some examples, a requesting device displays a visual representation of data. An authenticating device detects the presence of the visual representation of data. The authenticating device prompts a user to provide authorization information at the authenticating device. The authenticating device receives a set of one or more inputs. The authenticating device transmits information authorizing access to content on the requesting device.

Abstract: A machine learning model may be trained on a first task of puzzle solving before being tuned on a second task of image analysis. The training of the machine learning model may be self-supervised whereas the tuning of the machine learning model may be supervised. The training data may include a puzzle generated to include multiple imaging modalities. The puzzle may be generated by shuffling a position of the pieces forming an original image. The machine learning model may be trained to perform the first task by reassembling the pieces in the puzzle to generate a reconstruction of the original image. Upon being trained to perform the first task and tuned to perform the second task, the machine learning model may be deployed to perform the second task. The second task may be an image segmentation task such as tumor segmentation and a regression task such as survival prediction.

Abstract: Systems and methods for encoding multiple video streams with digital watermarking for adaptive bitrate streaming in accordance with embodiments of the invention are disclosed.

Abstract: Examples disclosed herein may involve (i) based on an analysis of 2D data captured by a vehicle while operating in a real-world environment during a window of time, generating a 2D track for at least one object detected in the environment comprising one or more 2D labels representative of the object, (ii) for the object detected in the environment: (a) using the 2D track to identify, within a 3D point cloud representative of the environment, 3D data points associated with the object, and (b) based on the 3D data points, generating a 3D track for the object that comprises one or more 3D labels representative of the object, and (iii) based on the 3D point cloud and the 3D track, generating a time-aggregated, 3D visualization of the environment in which the vehicle was operating during the window of time that includes at least one 3D label for the object.

Abstract: Systems and methods for real-time target validation during radiation treatment therapy based on real-time target displacement and radiation dosimetry measurements.

Abstract: The systems and methods disclosed herein provide determination of an orientation of a feature towards a reference target. As a non-limiting example, a system consistent with the present disclosure may include a processor, a memory, and a single camera affixed to the ceiling of a room occupied by a person. The system may analyze images from the camera to identify any objects in the room and their locations. Once the system has identified an object and its location, the system may prompt the person to look directly at the object. The camera may then record an image of the user looking at the object. The processor may analyze the image to determine the location of the user's head and, combined with the known location of the object and the known location of the camera, determine the direction that the user is facing. This direction may be treated as a reference value, or “ground truth.” The captured image may be associated with the direction, and the combination may be used as training input into an application.

Abstract: Systems and methods for generating a three-dimensional representation of a surface using frustrated total internal reflection. The system may obtain a two-dimensional image of an object in close proximity to an imaging surface. The intensity of the electromagnetic radiation received for individual points on the object may be determined. The system may determine a distance between the imaging surface and the object at each of the individual points based on a correlation between the electromagnetic radiation transmitted towards the imaging surface and the electromagnetic radiation reflected from the imaging surface. The determined intensity of the electromagnetic radiation may indicate the electromagnetic radiation reflected from the imaging surface. A three-dimensional representation of the object may be generated based on the two-dimensional image and/or the determined distances between the imaging surface and the object at each of the individual points.

Abstract: An approach for improving determining a significant slice associated with a tumor from a volume of medical images is disclosed. The approach is based on the annotation of tumor range and the slice index in which the tumor appears to have the largest area. The approach infer a tumor growth classifier on sliding window of the volume slices and creates a discrete integral function out of the classifier predictions. The approach applies post processing on the discrete integral function which can include a smoothing function and a bias correction. The approach selects the slice index of maximum value from the post processing step.

Abstract: The present disclosure relates to a data acquisition device and a configuration method. The device includes a channel, wherein the channel includes a data control panel and a plurality of detection components. At least one of the plurality of detection components is directly connected to the data control panel. The data control panel may be configured to identify the channel and send a configuration command to the plurality of detection components. The plurality of detection components may determine channel location numbers of the plurality of detection components based on the configuration command and send the channel location numbers to the data control panel. The data control panel may determine identification numbers for the plurality of detection components based on the channel location numbers and allocate the identification numbers to the plurality of detection components.

Abstract: In one embodiment, a method of machine learning and/or image processing for spectral object classification is described. In another embodiment, a device is described for using spectral object classification. Other embodiments are likewise described.

Abstract: A control device may obtain sensing data related to a paving material mat region laid by a screed assembly of a road paver. The control device may determine, based on the sensing data, a respective texture value and/or a respective height value associated with each portion of two or more portions of the paving material mat region. The control device may determine, based on the respective texture values and/or the respective height values of the paving material mat region, a finish value associated with the paving material mat region. The control device may cause, based on the finish value of the paving material mat region, one or more actions to be performed.

Abstract: The present disclosure relates to methods, systems, and non-transitory computer readable mediums for reconstructing an image. Image data may be obtained, wherein the image data may be generated by a detector array. A weighting window may be determined based on at least one parameter relating to the detector array. A first set of data may be determined based on the image data and the weighting window. An objective function associated with a target image may be determined based on the first set of data, wherein the objective function may include a first model, the first model may represent a difference between the target image and the first set of data, and the first model may be identified based on the first set of data. The target image may be reconstructed by performing a plurality of iterations based on the objective function.

Abstract: Systems for profile management and control are provided. A system may receive an instrument or image of an instrument. In some examples, data may be extracted from the instrument or image of the instrument and a document profile may be retrieved based on the extracted data. Images within the document profile may be evaluated to identify a type of document for each document. In some examples, a total number of documents of each type may be determined or identified. The total number of documents may be compared to a threshold. If the total number of documents is below the threshold, the documents or images in the profile may be maintained. If the total number of documents is at or above the threshold, in some examples, each document may be further evaluated to determine or identify documents or document images for deletion. In some arrangements, the profile may be refreshed and documents or images identified for deletion may be deleted.

Abstract: Methods for calculating a MetaKG signal are provided. The method including illuminating a region of interest in a sample with a near-infrared (NIR) light source and/or a visible light source. The region of interest includes a sample portion and background portion, each having a different set of optical characteristics. Images of the region of interest are acquired and processed to obtain metadata associated with the acquired images. MetaKG signals are calculated for the region of interest and for the background. The MetaKG signal for the background is used to adjust the MetaKG signal for the region of interest to provide a final adjusted MetaKG signal for the region of interest.