Abstract: The present invention discloses a stereo garage that comprises: a main body provided with a lifting shaft, wherein the lifting shaft is provided with an opening; a lifting platform located in the lifting shaft, wherein the lifting platform can ascend or descend in the lifting shaft along a height direction of the main body, such that the lifting platform can switch between an initial position and an end position, wherein the lifting platform can close the opening when the lifting platform is located in the initial position; an anti-falling device connected to the main body, wherein the anti-falling device comprises a blocking rod which can be switched between a locking position and an unlocking position; wherein, the blocking rod can block a movement of a vehicle when the blocking rod is located in the locking position, and the lifting platform can cause the blocking rod to be switched from the locking position to the unlocking position when the lifting platform comes into the initial position.

Abstract: A neural network is trained and implemented to simultaneously remove noise and artifacts from medical images using a Generalized noise and Artifact Reduction Network (“GARNET”) method for training a convolutional neural network (“CNN”) or other suitable neural network or machine learning algorithm. Noise and artifact realizations from phantom images are used to synthetically corrupt images for training. Corrupted and uncorrupted image pairs are used for training GARNET. Following the training phase, GARNET can be used to improve image quality of routine medical images by way of noise and artifact reduction.

Abstract: Provided are a method and apparatus for processing a deterministic networking (DetNet) data packet. The method includes: performing, by a DetNet node, format encapsulation on a data packet of a DetNet application flow when the DetNet application flow passes through a multiprotocol label switching (MPLS) network, wherein an encapsulated data packet comprises a label indication and a flow identifier header; and forwarding the encapsulated data packet in the MPLS network.

Abstract: A system and method for determining stenosis severity in a subject's vasculature using multi-energy computer tomography (MECT) imaging is provided. In some aspects, the method includes acquiring MECT data using a CT system, performing a material decomposition process on acquired MECT data to generate one or more material density maps, and selecting, using the one or more material density maps, one or more regions of interest (ROIs) encompassing at least one vessel cross-section. The method also includes measuring an iodine content in the one or more ROIs, and determining a stenosis severity based on the measured iodine content. The method further includes generating a report indicating the stenosis severity associated with the subject's vasculature.

Abstract: A glass tank furnace having a length to width ratio of no less than 2.3 and no greater than 2.8. The glass tank furnace includes one or more weirs and a plurality of bubbling tubes provided on a bottom of the glass tank furnace. The plurality of bubbling tubes are disposed before, behind, or on the weirs.

Abstract: Images are reconstructed from data acquired using an ultra-fast-pitch acquisition with a CT system. As an example, an ultra-fast-pitch acquisition mode in single-source helical CT (p?1.5) can be used to acquire data. A trained machine learning algorithm, such as a neural network, is used to reconstruct images in which artifacts associated with insufficient data acquired in the ultra-fast-pitch mode are reduced. An example neural network can include customized functional modules using both local and non-local operators, as well as the z-coordinate of each image, to effectively suppress the location- and structure-dependent artifacts induced by the ultra-fast-pitch mode. The machine learning algorithm can be trained using a customized loss function that involves image-gradient-correlation loss and feature reconstruction loss.

Abstract: A system and method is provided for performing material decomposition using a computed tomography (CT) system. The method includes acquiring CT imaging data of an object including data subsets corresponding to at least two different energy spectral bins and using the CT imaging data at each of the at least two different energy spectral bins to form a series of equations for basis material decomposition. The method also includes using a general physical constraint, which quantifies how each basis material in the object is mixed together to form the object, within the series of equations. The method also includes determining at least one basis material density of the object using the physical constraint and the CT imaging data and generating an image of the object using the CT imaging data and the mass densities of at least one basis material.

Abstract: Photography equipment, specifically a clamping and supporting apparatus for a smart mobile terminal, including an accommodating member and a mobile phone clamp assembly. The accommodating member includes an accommodating body and a connecting plate rotatably connected to the accommodating body. The mobile phone clamp assembly is disposed on the connecting plate and configured to be received in the accommodating body. The connecting plate rotates to allow the mobile phone clamp assembly to be received in the accommodating body. When the mobile phone clamp assembly is not in use, the connecting plate is rotated to allow the mobile phone clamp assembly to be received, so that space is saved and the accommodation and placement of the clamping and supporting apparatus are facilitated. The accommodating body is a handle, so that one can conveniently hold the accommodating body with one hand and open or close the connecting plate with the other hand.

Abstract: A fully image-based framework for CT image, or other medical image, quality evaluation and virtual clinical trial using deep-learning techniques is provided. This framework includes deep learning-based noise insertion, lesion insertion, and model observer, which enable efficient, objective, and quantitative image quality evaluation and virtual clinical trial directly performed on patient images.

Abstract: System and methods are provided for producing computed tomography (CT) images. In some aspects, a method includes obtaining medical image data sets acquired using the multiple energies of irradiating radiation and analyzing the medical image data sets for spatial and spectral features. The method also includes comparing the spatial and spectral features of the medical image data sets to identify similarities and using the similarities, weighting the medical image data sets to generate images of the subject having reduced noise compared to images of the subject produced from the medical image data sets without weighting.

Abstract: Systems and methods are provided for synthesizing information from multiple image series of different kernels into a single image series, and also for converting a single baseline image series of a kernel reconstructed by a CT scanner to image series of various other kernels, using deep-learning based methods. For multi-kernel synthesis, a single set of images with desired high spatial resolution and low image noise can be synthesized from multiple image series of different kernels. The synthesized kernel is sufficient for a wide variety of clinical tasks, even in circumstances that would otherwise require many separate image sets. Kernel conversion may be configured to generate images with arbitrary reconstruction kernels from a single baseline kernel. This would reduce the burden on the CT scanner and the archival system, and greatly simplify the clinical workflow.

Abstract: Embodiments of the present application disclose a method, device, system and server for acquiring and providing vehicle image data.

Abstract: A glass fiber tank kiln passage crown structure includes a chest wall brick, a supporting column built on a top of the chest wall brick, and a crown having an arch structure. Two ends of the crown are built on the supporting column, and a span of the crown is in a range from 0.5 meters to 4 meters.

Abstract: A fully image-based framework for CT image, or other medical image, quality evaluation and virtual clinical trial using deep-learning techniques is provided. This framework includes deep learning-based noise insertion, lesion insertion, and model observer, which enable efficient, objective, and quantitative image quality evaluation and virtual clinical trial directly performed on patient images.

Abstract: A clamping device for an intelligent mobile terminal includes a first clamping member provided with a first clamping portion; and a second clamping member slidably engaged with the first clamping member and provided with a second clamping portion, a space for clamping the intelligent mobile terminal being formed between the second clamping portion and the first clamping portion, wherein an end of the first clamping member away from the second clamping member in a sliding direction is provided with a male connector, and an end of the second clamping member away from the first clamping member in the sliding direction is provided with a female connector that matches the male connector.

Abstract: A glass tank furnace having a high melting rate. The ratio of the length of the glass tank furnace to the width thereof is 2.3 to 2.8. By reducing the area of a furnace and optimizing the length-to-width ratio thereof, the heat loss of the tank furnace is reduced. By designing an appropriate liquid glass tank depth, the temperature of a furnace bottom is improved and the quality of the liquid glass is guaranteed. By providing pure oxygen burners (3) and electrodes (7), sufficient energy is guaranteed, the melting capability and the heating efficiency of the tank furnace are improved, and energy consumption and the discharge amount of carbon dioxide are significantly reduced. Weirs (5) arranged on the furnace bottom improve the outlet temperature of the liquid glass, reduce energy consumption, lower the temperature of the furnace bottom in the electrode area, prolong the service life of the furnace bottom, and guarantee an increased proportion of auxiliary power.

Abstract: A system and method is provided for performing material decomposition using a computed tomography (CT) system. The method includes acquiring CT imaging data of an object including data subsets corresponding to at least two different energy spectral bins and using the CT imaging data at each of the at least two different energy spectral bins to form a series of equations for basis material decomposition. The method also includes using a general physical constraint, which quantifies how each basis material in the object is mixed together to form the object, within the series of equations. The method also includes determining at least one basis material density of the object using the physical constraint and the CT imaging data and generating an image of the object using the CT imaging data and the mass densities of at least one basis material.

Abstract: A system and method for determining stenosis severity in a subject's vasculature using multi-energy computer tomography (MECT) imaging is provided. In some aspects, the method includes acquiring MECT data using a CT system, performing a material decomposition process on acquired MECT data to generate one or more material density maps, and selecting, using the one or more material density maps, one or more regions of interest (ROIs) encompassing at least one vessel cross-section. The method also includes measuring an iodine content in the one or more ROIs, and determining a stenosis severity based on the measured iodine content. The method further includes generating a report indicating the stenosis severity associated with the subject's vasculature.

Abstract: System and methods are provided for producing computed tomography (CT) images. In some aspects, a method includes obtaining medical image data sets acquired using the multiple energies of irradiating radiation and analyzing the medical image data sets for spatial and spectral features. The method also includes comparing the spatial and spectral features of the medical image data sets to identify similarities and using the similarities, weighting the medical image data sets to generate images of the subject having reduced noise compared to images of the subject produced from the medical image data sets without weighting.

Abstract: Embodiments of the application provide a monitoring method, server and system and an image acquisition device capable of obtaining a first distance ratio of the horizontal distances from three WiFi detectors to a target person. The application is also capable of obtaining a second distance ratio of the horizontal distances from the three WiFi detectors to a WiFi terminal based on the signal strength of WiFi signals. The application determines the MAC address of the WiFi terminal of the target person by matching the second distance ratios of various WiFi terminals with the first distance ratio, and monitors the target person according to the MAC address. Thus, the application achieves continuous monitoring of the target person.