Abstract: The present disclosure provides a computer-implemented method which comprises a first step of obtaining an image data of the body portion from an ultrasound probe; a second step of analyzing the image data by use of machine learning and identifying a target and an evasion object; and a third step of determining the location of a final target, with reference to the information of the identified target and the evasion object. The final target is determined by at least one of a first information relating to the size of the target, a second information relating to the depth of the target, and a third information relating to the existence of an object in the straight path between the target and skin surface.

Abstract: Systems and methods for augmenting images can utilize one or more image augmentation models and one or more texture transfer blocks. The image augmentation model can process input images and one or more segmentation masks to generate first output data. The first output data and the one or more segmentation masks can be processed with the texture transfer block to generate an augmented image. The input image can depict a scene with one or more occlusions, and the augmented image can depict the scene with the one or more occlusions replaced with predicted pixel data.

Abstract: A method for lung nodule evaluation is provided. The method may include obtaining a target image including at least a portion of a lung of a subject. The method may also include segmenting, from the target image, at least one target region each of which corresponds to a lung nodule of the subject. The method may further include generating an evaluation result with respect to the at least one lung nodule based on the at least one target region.

Abstract: The present disclosure relates to a method, performed by a processor, for processing a blood vessel image from a blood vessel image, the method comprising the steps of: extracting a target blood vessel from a blood vessel image; determining a region of interest (ROI) in an extraction result of the target blood vessel on the basis of a first input received from a user; and within the determined ROI, identifying an error portion in the extraction result on the basis of a second input received from the user, and correcting the identified error portion.

Abstract: A patient-customized electrode array (EA) includes a plurality of electrodes, {Ei}, assembled in a pre-curved form, wherein the curvature of the EA at the i-th electrode Ei is characterized with a curvature that matches the curvature of the i-th point Pi of a structure curve in the cochlea of a patient where the i-th electrode Ei is to be placed, wherein i=1, 2, 3, . . . N, N is an integer greater than zero.

Abstract: A control method for an image processing apparatus that generates a plurality of pieces of album data including a common page, which is a page common to all of the plurality of pieces of album data, and an individual page, which is a page not common to all of the plurality of pieces of album data, includes performing control in such a manner that cover image data corresponding to an image to be placed in a cover of each album is selected as individual image data or common image data.

Abstract: Systems and methods are disclosed for assessing cardiovascular disease and treatment effectiveness based on adipose tissue. One method includes identifying a vascular bed of interest in a patient's vasculature; receiving a medical image of the patient's identified vascular bed of interest; identifying adipose tissue in the received medical image; receiving a geometric vascular model comprising a representation of the patient's identified vascular bed of interest; and computing an inflammation index associated with the geometric vascular model, using the identified adipose tissue.

Abstract: A localized evaluation network incorporates a discriminator acting as classifier, which may be included within a generative adversarial network (GAN). GAN may include a generative network such as U-NET for creating segmentations. The localized evaluation network is trained on image pairs including medical images of organs of interest and segmentation (mask) images. The network is trained to distinguish whether an image pair does or does not represent the ground truth. GAN examines interior layers of the discriminator and evaluates how much each localized image region contributes to the final classification. The discriminator may analyze regions of the image pair that contribute to a classification by analyzing layer weights of the machine learning model. Disclosed embodiments include a visual attribute, such as a heat map, that represents contributions of localized regions of a contour to an overall confidence score. These localized regions may be highlighted and reported for quality assurance review.

Abstract: According to one embodiment, a medical image processing apparatus includes first specifier, second specifier, determiner and display controller. First specifier collates an ischemic region calculated from a blood vessel visualized into a three-dimensional image in a plurality of phases with a dominating region of the blood vessel, and specifies a culprit vessel in the ischemic region. Second specifier specifies a culprit stenosis in the culprit vessel based on a pressure index calculated from the blood vessel. Determiner determines a connection position to connect a bypass vessel that makes a detour around the culprit stenosis. Display controller displays the determined connection position on a display.

Abstract: The present disclosure includes systems and methods for deriving certain characteristics of the patient's body related to motion from captured motion data. The characteristics may be used to compare the characteristics of the supposed injury to the characteristics of a normally functioning body part as well as the functions of an injured body part. The present disclosure provides a reliable and reproducible way to determine whether a supposed injury is a feigned or exaggerated injury or an actual injury.

Abstract: A method for processing image noise in a compression process and a circuit system thereof are provided. The circuit system receives an image that is compressed in a specific compression format, and obtains pixel values after the image is decompressed. Differences of pixel values between pixels adjacent to each other can be calculated. A specific area of the image can be divided into multiple sections. A maximum pixel value and a minimum pixel value for each area are used to obtain a regional maximum difference. The regional maximum difference is used to determine whether or not to perform an image-denoising process on the areas such as a flat area or a high-frequency area. Differences among the adjacent pixels can be adjusted according to a weighted average brightness of the adjacent pixels. The image-denoising process is performed on the areas, and an image with reduced noise is finally outputted.

Abstract: A perception system, comprising a set of reference sensors; a set of test sensors and a computing device, which is configured for receiving first training signals from the set of reference sensors and receiving second training signals from the set of test sensors, the set of reference sensors and the set of test sensors simultaneously exposed to a common scene; processing the first training signals to obtain reference images containing reference depth information associated with the scene; and using the second training signals and the reference images to train a neural network for transforming subsequent test signals from the set of test sensors into test images containing inferred depth information.

Abstract: Methods and systems are provided for reconstructing images from measurement data using one or more deep neural networks according to a decimation strategy. In one embodiment, a method for reconstructing an image using measurement data comprises, receiving measurement data acquired by an imaging device, selecting a decimation strategy, producing a reconstructed image from the measurement data using the decimation strategy and one or more deep neural networks, and displaying the reconstructed image via a display device. By decimating measurement data to form one or more decimated measurement data arrays, a computational complexity of mapping the measurement data to image data may be reduced from O(N4), where N is the size of the measurement data, to O(M4), where M is the size of an individual decimated measurement data array, wherein M<N.

Abstract: The specification discloses image and data processing methods and apparatuses. The method includes: obtaining a source pose and texture information according to a source image; obtaining a first synthetic image according to the source image, a target pose, and the source pose; obtaining a residual map according to the texture information and the first synthetic image; and obtaining a second synthetic image according to the first synthetic image and the residual map. The specification resolves the technical problem of lacking a sense of reality in a synthetic image due to loss of texture details in feature extraction during character action transfer in the existing technologies.

Abstract: An electronic device and a method are provided for description parameter based modification of images. The method includes determining a description parameter associated with an image; determining a cluster including a portion related to the description parameter of the image to be modified; and modifying the portion of the image based on the description parameter.

Abstract: An embodiment of the disclosure provides a live steam sampling method and device and electronic equipment, which belong to the technical field of image processing. The method comprises: extracting multi-frame sampled images from live stream; screening out forward similar images from all sampled images, wherein the forward similar images are sampled images similar to a sampled image of a previous adjacent frame; and taking the rest of the sampled images, except from the forward similar images, in all sampled images as sampled images of the live stream. According to the solution of the disclosure, a solution of effectively eliminating the forward similar images in sampling operation based on a FPS is realized, thereby avoiding the leakage conditions, reducing total workload of sampling and checking, and improving efficiency of live stream sampling.

Abstract: The present disclosure relates to an object selection system that accurately detects and automatically selects target instances of user-requested objects (e.g., a query object instance) in a digital image. In one or more embodiments, the object selection system can analyze one or more user inputs to determine an optimal object attribute detection model from multiple specialized and generalized object attribute models. Additionally, the object selection system can utilize the selected object attribute model to detect and select one or more target instances of a query object in an image, where the image includes multiple instances of the query object.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media that allow a user to easily obtain accurate image-based measurements of physical items, including one or more crops. Also disclosed herein are systems, methods and non-transitory computer-readable storage media that utilize the accurate measurements to generate one or more derived metric.

Abstract: An influence on object expression performed at a transmission destination is reduced. A position information reception unit 11 of an information integration device 1 receives, regarding objects which are measured by a plurality of sensors from a plurality of locations and overlap in any of the locations, position information for each location on areas of the objects. A position information integration unit 13 calculates smallest rectangles or largest rectangles surrounding the objects by using the position information for each location.

Abstract: A fingerprint sensor device and a method of making a fingerprint sensor device. As non-limiting examples, various aspects of this disclosure provide various fingerprint sensor devices, and methods of manufacturing thereof, that comprise an interconnection structure, for example a bond wire, at least a portion of which extends into a dielectric layer utilized to mount a plate, and/or that comprise an interconnection structure that extends upward from the semiconductor die at a location that is laterally offset from the plate.