Abstract: Human mesh model recovery may utilize prior knowledge of the hierarchical structural correlation between different parts of a human body. Such structural correlation may be between a root kinematic chain of the human body and a head or limb kinematic chain of the human body. Shape and/or pose parameters relating to the human mesh model may be determined by first determining the parameters associated with the root kinematic chain and then using those parameters to predict the parameters associated with the head or limb kinematic chain. Such a task can be accomplished using a system comprising one or more processors and one or more storage devices storing instructions that, when executed by the one or more processors, cause the one or more processors to implement one or more neural networks trained to perform functions related to the task.

Abstract: Methods and systems for guiding a patient for a medical examination using a medical apparatus. For example, a computer-implemented method for guiding a patient for a medical examination using a medical apparatus includes: receiving an examination protocol for the medical apparatus; determining a reference position based at least in part on the examination protocol; acquiring a patient position; determining a deviation metric based at least in part on comparing the patient position and the reference position; determining whether the deviation metric is greater than a pre-determined deviation threshold; and if the deviation metric is greater than a pre-determined deviation threshold: generating a positioning guidance based at least in part on the determined deviation metric, the positioning guidance including guidance for positioning the patient relative to the medical apparatus.

Abstract: The present disclosure relates to systems and methods for imaging. The method may include obtaining a real-time representation of a subject. The method may also include determining at least one scanning parameter associated with the subject by automatically processing the representation according to a parameter obtaining model. The method may further include performing a scan on the subject based at least in part on the at least one scanning parameter.

Abstract: A system and method for visual anomaly localization in a test image includes generating, in plurality of scaled iterations, attention maps for a test image using a trained classifier network, using image-level. A current attention map is generated using an inversion of the classifier network on a condition that a forward pass of the test image in the classifier network detects a first class. One or more attention regions of the current attention map may be extracted and resized as a sub-image. For each scaled iteration, extraction of one or more regions of a current attention map is performed on a condition that the current attention map is significantly different than the preceding attention map. Visual localization of a region for the class in the test image is based on one or more of the attention maps.

Abstract: A method of expanding a visual learning database in a computer by teaching the computer includes providing a series of training images to the computer wherein each series includes three images with each image falling within a unique image domain and with each image domain representing a possible combination of a first attribute and a second attribute with a first image domain including the first attribute and the second attribute in a first state (X=0, Y=0), a second image domain including the first attribute in a second state and the second attribute in the first state (X=1, Y=0), and a third image domain including the first attribute in the first state and the second attribute in the second state (X=0, Y=1).

Abstract: An apparatus is configured to receive input image data corresponding to output image data of a first radiology scanner device, translate the input image data into a format corresponding to output image data of a second radiology scanner device and generate an output image corresponding to the translated input image data on a post processing imaging device associated with the first radiology scanner device. Medical images from a new scanner can be translate to look as if they came from a scanner of another vendor.

Abstract: Improved formulations of electrophoretic media that can be incorporated into displays, front plane laminates, inverted front plane laminates, or color changing films. The formulations include a non-polar fluid, a plurality of first charged particles, and charge control agents (CCA) including a quaternary amine and an unsaturated polymeric tail comprising monomers of at least 10 carbon atoms in length. The formulations show improved switching speeds, as well as a larger dynamic range at low temperatures (i.e., below about 0° C.), where compared to state-of-the-art electrophoretic media.

Abstract: Systems, methods, and computer-readable media are described for determining the orientation of a target object in an image and iteratively reorienting the target object until an orientation of the target object is within an acceptable threshold of a target orientation. Also described herein are systems, methods, and computer-readable media for verifying that an image contains a target object.

Abstract: A method for medical imaging is provided. The method may include automatically determining that a positioning procedure of a subject has been finished based on image data of the subject captured by an image capturing device. The method may also include obtaining status information of a medical device. The method may further include causing the medical device to perform a scan on the subject based on a determination result that the positioning procedure of the subject has been finished, the status information of the medical device, and a starting signal of the scan.

Abstract: The present embodiments relate to automatically estimating a three-dimensional pose of an object from an image captured using a camera with a structured light sensor. By way of introduction, the present embodiments described below include apparatuses and methods for training a system for and estimating a pose of an object from a test image. Training and test images are sampled to generate local image patches. Features are extracted from the local image patches to generate feature databased used to estimate nearest neighbor poses for each local image patch. The closest nearest neighbor pose to the test image is selected as the estimated three-dimensional pose.

Abstract: Abnormality detection within a defined area includes obtaining a plurality of images of the defined area from image-capture devices. An extent of deviation of one or more types of products from an inference of each of the plurality of images is determined using a trained neural network. A localized dimensional representation is generated in a portion of an input image associated with a first location of the plurality of locations, based on gradients computed from the determined extent of deviation. The generated localized dimensional representation provides a visual indication of an abnormality located in the first location within the defined area. An action associated with the first location is executed based on the generated dimensional representation for proactive control or prevention of occurrence of undesired event in the defined area.

Abstract: A standalone image reconstruction device is configured to reconstruct the raw signals received from a radiology scanner device into a reconstructed output signal. The image reconstruction device is a vendor neutral interface between the radiology scanner device and the post processing imaging device. The reconstructed output signal is a user readable domain that can be used to generate a medical image or a three-dimensional (3D) volume. The apparatus is configured to reconstruct signals from different types of radiology scanner devices using any suitable image reconstruction protocol.

Abstract: Data samples are transmitted from a central server to at least one local server apparatus. The central server receives a set of predictions from the at least one local server apparatus that are based on the transmitted set of data samples. The central server trains a central model based on the received set of predictions. The central model, or a portion of the central model corresponding to a task of interest, can then be sent to the at least one local server apparatus. Neither local data from local sites nor trained models from the local sites are transmitted to the central server. This ensures protection and security of data at the local sites.

Abstract: Healthcare services can be automated utilizing a system that recognizes at least one characteristic of a patient based on images of the patient acquired by an image capturing device. Relying on information extracted from these images, the system may automate multiple aspects of a medical procedure such as patient identification and verification, positioning, diagnosis and/or treatment planning using artificial intelligence or machine learning techniques. By automating these operations, healthcare services can be provided remotely and/or with minimum physical contact between the patient and a medical professional.

Abstract: Improved formulations of electrophoretic media that can be incorporated into displays, front plane laminates, inverted front plane laminates, or color changing films. The formulations include a non-polar fluid, a plurality of first charged particles, and charge control agents (CCA) including a quaternary amine and an unsaturated polymeric tail comprising monomers of at least 10 carbon atoms in length. The formulations show improved switching speeds, as well as a larger dynamic range at low temperatures (i.e., below about 0° C.), where compared to state-of-the-art electrophoretic media.

Abstract: Quinacridone pigments that are surface-functionalized with glycidyl methacrylate, maleic anhydride, or 4-methacryloxyethyl trimellitic anhydride to create a functionalized pigment. The functional groups are then activated to bond hydrophobic polymers, thereby coating the pigment with the hydrophobic polymers. The quinacridone pigments can be used for a variety of applications. They are well-suited for use in electro-optic materials, such as electrophoretic media for use in electrophoretic displays.

Abstract: Methods and systems for providing guidance for adjusting a target. For example, a computer-implemented method for providing guidance for adjusting a target includes: receiving, by a neural network, a reference image; receiving, by the neural network, the target image, the target image being related to a position of a target; determining a similarity metric based at least in part on information associated with the reference image and information associated with the target image by the neural network; generating a target attention map corresponding to the target image based at least in part on the similarity metric; outputting the target image and the target attention map; and providing a guidance for adjusting the position of the target based at least in part on the target image and the target attention map.

Abstract: A method for training a generative network that is configured for converting cluttered images into a representation of the synthetic domain and a method for recovering an object from a cluttered image.

Abstract: The present disclosure generally provides systems and methods for situation awareness. When executing a set of instructions stored in at least one non-transitory storage medium, at least one processor may be configured to cause the system to perform operations including obtaining, from at least one of one or more sensors, environmental data associated with an environment corresponding to a first time point, generating a first static global representation of an environment corresponding to the first time point based at least in part on the environmental data, generating a first dynamic global representation of the environment corresponding to the first time point based at least in part on the environmental data, and estimating, based on the first static global representation and the first dynamic global representation, a target state of the environment at a target time point using a target estimation model.

Abstract: Systems, methods, and computer-readable media are described for training a neural network to perform keypoint detection and view-invariant keypoint representation generation. A locally learned database of three-dimensional (3D) keypoint landmarks extracted from a sample set of training depth images can be populated with view-invariant keypoint representations of the keypoint landmarks stored in association with corresponding 3D locations of the keypoint landmarks. The populated 3D keypoint landmark database can be used to find 3D keypoints that match 2D keypoints extracted from a test depth image having an unknown pose. A parameter estimation algorithm can be executed on the 3D locations of the matching keypoint landmarks to determine a pose corresponding to the test depth image.