Abstract: In a radio-frequency circuit, a first switch is connected to an antenna terminal. A second switch is connected to the first switch and is connected to the antenna terminal via the first switch. A first filter is connected to the first switch without having the second switch interposed therebetween and allows a radio-frequency signal of a first communication band to pass through the first filter. A second filter is connected to the first switch via the second switch and allows a radio-frequency signal of a second communication band to pass through the second filter. The second communication band is higher than the first communication band. The radio-frequency circuit further includes an inductor. The inductor is not connected in series with the first filter and is connected in series with the first switch and the second switch between the first switch and the second switch.

Abstract: Embodiments of the present application provide a tissue boundary determination apparatus and method. The tissue boundary determination method includes acquiring multiple slice images of multiple positions of a tissue to be examined, determining, with regard to at least one first selected slice image of the multiple slice images, a tissue boundary on the first selected slice image, and determining, according to the tissue boundary on the first selected slice image, tissue boundaries on a predetermined number of other slice images adjacent to the first selected slice image. Therefore, an accurate tissue (such as malignant tumor) boundary may be acquired efficiently so as to provide a reference basis for analysis on internal and external tissue of a tumor.

Abstract: A wearable device may compress the skin of a user when worn, which may affect values determined using sensors of the device. To determine the effect of skin compression on the values, a time-of-flight signal, images, or frames of video data that depict a portion of the body having indentations from wearing the device may be acquired. Characteristics of the images, such as shadows associated with the indentations, may be processed using a machine learning algorithm or mathematical function to determine a depth of various portions of the indentations. Depth data from the time of flight signal may be used to refine or modify these determined depths. The amount of skin compression associated with the indentations may be used to modify signals acquired using sensors, or output a recommendation for a band or other method for securing the device.

Abstract: A stream of virtual topograms, in particular live virtual topograms, is predicted. Sets of surface data of an outer surface of a subject are continuously received. Based on each received set of surface data a (live) virtual topogram is continuously generated by a trained machine learning algorithm (MLA). Thereto, a representation of body landmarks is updated based on each received set of surface data by a trained body marker detector (BMD), of the trained MLA, and the (live) virtual topogram is predicted based on the updated spatial marker map and on the corresponding set of surface data by a trained topogram generator (TG) of the trained MLA.

Abstract: A device may receive images of a patient, and may perform segmentation of surfaces on the images to create a 3D model. The device may identify normal tissue regions and atrial fibrosis (AF) regions in the 3D model, and may divide the 3D model into the normal tissue regions and the AF regions. The device may assign first cell and tissue properties to the normal tissue regions, and may assign second cell and tissue properties to the AF regions. The device may perform simulations on the normal tissue regions and the AD regions, based on the first and second cell and tissue properties, to generate simulation results, and may extract first features from the simulation results. The device may extract second features from the images, and may process the first and second features, with a model, to select a feature that is predictive of atrial fibrillation recurrence.

Abstract: Systems and methods related to combing multiple images are disclosed. An example method of combining multiple images obtained by an endoscope includes obtaining a first input image formed from a first plurality of pixels, wherein a first pixel of the plurality of pixels includes a first characteristic having a first value. The method also includes obtaining a second input image formed from a second plurality of pixels, wherein a second pixel of the second plurality of pixels includes a second characteristic having a second value. The method also includes subtracting the first value from the second value to generate a motion metric and generating a weighted metric map of the second input image using the motion metric.

Abstract: In certain aspects, a system includes a first filter, a second filter, a dummy load, and a switching circuit coupled to the first filter, the second filter, and the dummy load, and coupled to a first antenna and a second antenna. In a first mode, the switching circuit couples the first filter and the second filter to the first antenna, and, in a second mode, the switching circuit couples the first filter and the third filter to the first antenna and couples the second filter to the second antenna. In certain aspects, the dummy load includes a third filter.

Abstract: Systems and methods for medical image registration are provided. A first input medical image and a second input medical image of one or more anatomical objects are received. For each respective anatomical object of the one or more anatomical objects, a region of interest comprising the respective anatomical object is detected in one of the first input medical image or the second input medical image, the region of interest is extracted from the first input medical image and from the second input medical image, and a motion distribution of the respective anatomical object is determined from one of the region of interest extracted from the first input medical image or the region of interest extracted from the second input medical image using a motion model specific to the respective anatomical object. The first input medical image and the second input medical image are registered based on the motion distribution of each respective anatomical object of the one or more anatomical objects to generate a fused image.

Abstract: Provided is a communication control apparatus configured to control communication of a flying body configured to form a wireless communication area by applying a beam toward the ground to provide wireless communication service for a user terminal in the wireless communication area. The communication control apparatus comprises an inner area forming unit configured to form an inner wireless communication area having a radius of about 100 km or shorter; and an outer area forming unit configured to form, on an outer side of the inner wireless communication area, an outer wireless communication area constituted by an outer peripheral cell, the outer peripheral cell having a radius of about 50 km or shorter.

Abstract: A method of relating an object to a coordinate system, the object being supported by a support element, and the object and the support element being housed within a housing, includes engaging a registration element with the object or the support element, conducting an optical surface scan of the object and the registration element, using an optical scanner, to form a three-dimensional surface image of the object, the three-dimensional surface image having the coordinate system associated therewith, with the registration element being associated with the coordinate system, and correlating the object with the registration element in the three-dimensional surface image so as to register the object with the coordinate system. Associated methods and systems are also provided.

Abstract: It is judged that a relevant tool is lost at a second time point after the elapse of a certain amount of time or longer after a first time point when it is judged that the tool is not recognized at all in images; and regarding the tool which is judged to have been lost, trace data corresponding to heads-up time, which is immediately before the first time point to immediately after the first time point, is read with reference to a corresponding identifier and a movement locus of the tool based on the trace data is displayed on a screen.

Abstract: A model generating apparatus includes a measurement unit and a change unit. The measurement unit measures a size of an object appearing on an image included in data set. The change unit changes, based on a distribution of the size, a layer to be connected to a detection unit of a Convolutional Neural Network (CNN) for detecting an object appearing on the image, among layers for extracting feature included in the CNN.

Abstract: Systems, methods, and devices for reconstructing an image is provided. An imaging device may be oriented at one or more poses and an image may be received at each of the one or more poses to form a set of images. Pose information may be received at each of the one or more poses. The set of images and the pose information may be inputted into a reconstruction model to generate a three-dimensional representation of the one or more anatomical elements.

Abstract: According to one embodiment, a compact broadband radio frequency (RF) frontend circuit includes a number of single-channel transceivers, a number of analog to digital converters (ADCs), where each of the ADCs is coupled to one of the single-channel transceivers, a number of digital to analog converters (DACs), where each of the DACs is coupled to one of the single-channel transceivers, and a digital signal processing (DSP) unit coupled to the ADCs and the DACs. The DSP unit is configured to generate a first set of digital data streams simultaneously and each of the first set of digital data streams is converted by a respective one of the DACs into an analog data stream to be transmitted to a remote device by a respective one of the single-channel transceiver.

Abstract: A personalized and intrinsically valuable jewelry form factor or greeting card that includes electronic functionality. In an embodiment, one form factor is metallic, rectangular device with overall thickness of 3 mm that is credit-card sized. Embedded inside the form factor are electronic components giving rise to its functionality such as processing, data storage, messaging display, user input, wireless charging facilities, battery compactly disposed inside of a 2 mm cavity. Further, the form factor provides strength with a wall thickness of 0.5 mm and made of titanium, or the like.

Abstract: Systems and methods for automatically detecting, classifying, and processing objects captured in an images or videos are provided. In one embodiment, the system receives an image from an image source and detects one or more objects in the image. The system performs a high-level classification of the one or more objects in the image. The system performs a specific classification of the one or more objects, determines a price of the one or more objects, and generates a pricing report comprising a price of the one or more objects. In another embodiment, the system captures at least one image or video frame and classifies an object present in the image or video frame using a neural network. The system adds the classified object and an assigned object code to an inventory and processes the inventory to assign the classified object a price.

Abstract: In various examples, a two-dimensional (2D) and three-dimensional (3D) deep neural network (DNN) is implemented to fuse 2D and 3D object detection results for classifying objects. For example, regions of interest (ROIs) and/or bounding shapes corresponding thereto may be determined using one or more region proposal networks (RPNs)—such as an image-based RPN and/or a depth-based RPN. Each ROI may be extended into a frustum in 3D world-space, and a point cloud may be filtered to include only points from within the frustum. The remaining points may be voxelated to generate a volume in 3D world space, and the volume may be applied to a 3D DNN to generate one or more vectors. The one or more vectors, in addition to one or more additional vectors generated using a 2D DNN processing image data, may be applied to a classifier network to generate a classification for an object.

Abstract: The present invention discloses methods and systems for communicating at a cellular router between a first wireless communication module and a first subscriber identity module (SIM). The cellular router receives a first request from a first wireless communication module and encapsulates the first request in a first modified request. The cellular router then sends the first modified request to a first SIM card in a first communication apparatus and waits for a first modified reply. While waiting for the first modified reply the cellular router sends at least one halt message to the first wireless communication module after a first time threshold. After receiving the first modified reply, the cellular router decapsulates the first modified reply to retrieve a first reply and sends the first reply to the first wireless communication module where the first modified reply is a reply to the first modified request.

Abstract: Certain embodiments of the present disclosure relate to a monitoring device that includes a housing, contactless sensors coupled to the housing, and a processing device disposed in the housing. In at least one embodiment, the monitoring device is configured to measure pulse wave velocity in a subject.

Abstract: Provided is an information processing device that is interposed between an imaging control device and an image management device in communication. The information processing device including an abnormality detector and a first hardware processor. The abnormality detector performs detection of an abnormality in a medical image received from the imaging control device. The first hardware processor that determines, based on a result of the detection by the abnormality detector, content or a destination of transmission of the medical image or the result of the detection.