Abstract: A tissue analysis system may include an ultrasound device to stimulate tissue with ultrasound waves causing the tissue to vibrate and produce a vibration signature, a vibration detector configured to detect the vibration signature, and a signal analysis processor. The signal analysis processor may be configured according to computer-executable instructions for accessing a signature library storing a plurality of vibration signatures each linked to one of a plurality of known tissues having a known identity, comparing the vibration signature of the tissue with the stored vibration signatures of the signature library, determining if a match between the vibration signature of the tissue and a stored vibration signature of the signature library is present and, if the match is present, determining an identity of the tissue based on the known identity of the known tissue having the matching stored vibration signature.

Abstract: In an object detection device for detecting an object, a single sensor unit includes a light emitting unit and a light receiving unit. The light receiving unit includes a two-dimensional array of light receiving elements and outputs a light reception signal in response to a light reception state of a set of the light receiving elements for each pixel. The sensor unit is configured to, based on the light reception signals, acquire first information indicating reception intensity of the reflected light at each pixel, second information indicating reception intensity of background light that is light other than the reflected light, at each pixel, and third information indicating a distance to the object at each pixel as a pixel value of the pixel. A detection unit is configured to use all of the first to third information included in the pixel values of the respective pixels to detect the object.

Abstract: A medical image processing device includes: a first captured image acquisition unit configured to acquire a first left-eye image and a first right-eye image; a second captured image acquisition unit configured to acquire a second left-eye image and a second right-eye image; a superimposed image generation unit configured to superimpose corresponding pixels of the first left-eye image and the second left-eye image on each other to generate a left-eye fluorescence superimposed image and superimpose corresponding pixels of the first right-eye image and the second right-eye image on each other to generate a right-eye fluorescence superimposed image; and a display controller configured to generate a display image from the first left-eye and right-eye images, the second left-eye and right-eye images, the left-eye and the right-eye fluorescence superimposed images, wherein the display image includes a stereoscopically observable three-dimensional fluorescence superimposed image generated from the left-eye and the ri

Abstract: A medical information processing system according to an embodiment includes processing circuitry and a display. On the basis of one of the type of at least one abnormality detection algorithm to which a medical image related to an examined subject is to be input and information relevant to an abnormality detected by inputting the medical image to the abnormality detection algorithm, the processing circuitry judges whether or not urgency is present in a disorder related to the abnormality. When it is determined that the urgency is present, the display displays, in an examination list of examination orders, assessment information related to assessing the abnormality and urgency information indicating the urgency so as to be positioned adjacent to any of the examination orders related to the abnormality.

Abstract: A method and an apparatus for three-dimensional reconstruction. Images of the reconstruction space captured by N cameras are acquired as N current images in response to an object entering the reconstruction space. Foreground-background differences of all position points in the N current images are obtained according to the N current images and N corresponding initial background images captured by the N cameras when the reconstruction space is empty. Corresponding foreground-background differences of position points in the N current images are fused according to a corresponding relationship between all position points in the N current images and all position points in the reconstruction space, to obtain a foreground-background difference of each position point in the reconstruction space.

Abstract: Methods and systems for manually assisted definition of vascular features are described. In some embodiments, a method provides for editing of vascular paths by enabling a user to drag an erroneously segmented region of a selected vascular path into alignment with a more correctly segmented position that is depicted as a blood vessel in a vascular image. The method may use an energy function, defined as a function of position along the segmentation of the selected blood vessel, to determine how a vascular path is to be moved based on dragging motions provided by the user. In some instances, non-zero regions of the energy function are set based on the position of the selected region.

Abstract: A method of reading a medical image by a computing device operated by at least one processor is provided. The method includes obtaining an abnormality score of the input image using an abnormality prediction model, filtering the input image so as not to be subsequently analyzed when the abnormality score is less than or equal to a cut-off score based on the cut-off score which makes a specific reading sensitivity; and obtaining an analysis result of the input image using a classification model that distinguishes the input image into classification classes when the abnormality score is greater than the cut-off score.

Abstract: A medical imaging communication system generates an automated report for a medical image corresponding to a patient. The system receives one or more medical images for a patient. The system applies a model to identify an abnormality in the received one or more medical images. The model is configured to determine a likelihood score for the presence of the abnormality in the one or more medical images. If the likelihood score is above a threshold value, the system generates an automated report indicating the type of abnormality identified in the received one or more medical images. The automated report is then provided to a viewing user (e.g., a medical professional viewing the one or more medical images).

Abstract: A method for detecting road edges at a predetermined intersection, comprising: receiving, by the controller, aerial imagery data about the predetermined intersection; receiving, by the controller, vehicle telemetry data from at least one vehicle passing through the predetermined intersection; detecting, using the aerial imagery data and generative adversarial networks (GANs) executed on the controller, road edges at the predetermined intersection; classifying, using the vehicle telemetry data and a random forest classifier (RFC) executed on the controller, each vehicle trajectory passing through the predetermined intersection with a label corresponding to a unique maneuver to create a maneuver labeling at the predetermined intersection; constructing, using the maneuver labeling determined by the RFC and the road edges, a probabilistic finite state automata (PFSA) to pair inbound lanes with outbound lanes at the predetermined intersection; and determining lane edges at the predetermined intersection using a ho

Abstract: An image diagnosis supporting device includes a model reader that reads an image diagnostic model that outputs a diagnostic result for a diagnostic image that is an input medical image, a storage unit that stores facility data that is a plurality of medical images associated with diagnostic results held in a facility, and an adjuster that adjusts, based on the facility data, the image diagnostic model or the diagnostic image input to the image diagnostic model.

Abstract: A system includes a number of transducers configured to transmit ultrasound signals directed to a target blood vessel and receive echo information associated with the transmitted ultrasound signals. The system also includes a processing device configured to process the echo information, generate ultrasound images of the blood vessel at a number of locations and generate an estimated diameter of the blood vessel at the locations. The processing device is also configured to output image information associated with the blood vessel and output a maximum estimated diameter of the blood vessel or the estimated diameters at the number of locations based on the image information.

Abstract: Systems and methods for generating a synthetic image are provided. An input medical image in a first modality is received. A synthetic image in a second modality is generated from the input medical image. The synthetic image is upsampled to increase a resolution of the synthetic image. An output image is generated to simulate image processing of the upsampled synthetic image. The output image is output.

Abstract: An image reconstruction apparatus according to an embodiment includes a processing circuitry configured to reconstruct at least one image from a plurality of pieces of k-space data acquired in a time direction. The processing circuitry performs image estimation calculation that reconstructs estimated images sharing the k-space data in the time direction, and adaptation calculation that adapts the estimated images to prior knowledge in the time direction.

Abstract: The invention provides methods and apparatus for image processing that perform image segmentation on data sets in two- and/or three-dimensions so as to resolve structures that have the same or similar grey values (and that would otherwise render with the same or similar intensity values) and that, thereby, facilitate visualization and processing of those data sets.

Abstract: Systems and methods are provided for utilizing histogram views for improved visualization of three-dimensional (3D) medical images. Imaging data obtained during medical imaging examination of a patient may be processed, with the imaging data corresponding to a particular medical imaging technique. At least one medical image may be generated based on processing of the imaging data. Histogram data may be generated based on the at least one medical image. At least one histogram may be displayed along with the at least one medical image or a projection of the at least one medical image, with the at least one histogram including or being is based on the histogram data, and with the at least one histogram being displayed next to and aligned with the at least one medical image or the projection of the at least one medical image.

Abstract: The present disclosure describes imaging systems configured to generate adaptive scanning protocols based on anatomical features and conditions identified during a prenatal scan of an object. Systems may include an ultrasound transducer configured to acquire echo signals responsive to ultrasound pulses transmitted toward a target region. Processors coupled with the transducer can generate an image frame from the echoes and provide the image frame to a first neural network. The first neural network may be configured to identify an anatomical feature in the image frame. An indication of the anatomical feature may be provided a second neural network. The second neural network may then determine an anatomical measurement to be obtained based, in part, on the feature identified. The processors may be further configured to cause an indicator of the anatomical measurement to be obtained to be displayed on a user interface.

Abstract: A method and system perform single phase and multi-phase contour refinement of lesions. The method includes receiving a three dimensional input mask; receiving input slices from the medical images including a lesion; cropping the input slices with the input mask; performing lesion contour refinement for the cropped input slices and the input mask to obtain a predicted mask; and storing the predicted mask that includes 3D lesion contour refinement. A multiphase method includes deforming the 3D input mask from the reference phase to a target phase or warping the input slices from the target phase to the reference phase before contour refinement. The warped images generate an output mask in the reference phase coordinate system that is then deformed to the target phase coordinate system for display.

Abstract: A parking space recognition system includes an external environment information acquiring device and a parking space candidate detecting device. The parking space candidate detecting device includes: a virtual line calculating unit configured to calculate a virtual line connecting road side ends of parking space lines adjacent to each other; an angle calculating unit configured to calculate an angle between the virtual line and one of the parking space lines; a parking type determining unit configured to determine a parking type; and a parking space candidate setting unit configured to set at least one provisional parking space in an area between the parking space lines based on positions of the parking space lines, and to set an available parking area among the provisional parking space to the parking space candidate.

Abstract: Disclosed herein are a system and method for assisting the verification of the contouring of medical images. A system for assisting the verification of the contouring of medical images according to an embodiment of the present invention receives a medical image set including a plurality of medical images via the communication interface, receives the result information of contouring performed on a plurality of regions of interest (ROIs) on the plurality of medical images in the medical image set via the communication interface, calculates the feature value of each of the plurality of ROIs, corresponding to the result information of the contouring, for each of the plurality of medical images, and displays the boundary of each of the plurality of ROIs corresponding to the result information of the contouring by projecting the boundary onto a reference plane.

Abstract: To obtain a predictive model that shows a diagnostic prediction result with higher accuracy and high medical validity. A medical imaging apparatus includes an imaging unit that collects an image signal of an inspection target, and an image processing unit that generates first image data from the image signal and performs image processing of the first image data. The image processing unit includes a feature quantity extraction unit that extracts a first feature quantity from the first image data, a feature quantity abstraction unit that abstracts the first feature quantity to extract a second feature quantity, a feature quantity conversion unit that converts the second feature quantity into a third feature quantity extracted by second image data, and an identification unit that uses the converted third feature quantity to calculate a predetermined parameter value.