Abstract: This application relates to computing circuitry (200), in particular for analogue computing circuitry suitable for neuromorphic computing. The circuitry (200) has a plurality of memory cells (201), each memory cell having an input electrode (201) for receiving a cell input signal and an output (203P, 203N) for outputting a cell output signal (IP, IN), with first and second paths connecting the input electrode to the output. The cell output signal thus depends on a differential current between the first and second paths due to the cell input signal. Each memory cell also comprises at least one programmable-resistance memory element (204) in each of the first and second paths and is controllable, by selective programming of the programmable-resistance memory elements, to store a data digit that can take any of at least three different values.

Abstract: An image processing apparatus includes an acquisition unit configured to acquire image data, a calculation unit configured to calculate, for each unit region of the image data, a confidence that the unit region is an extraction subject, the confidence as the extraction subject being calculated for each unit region of the image data by inputting the image data into a trained model of a neural network that has been trained using images of an existing extraction subject or a region of interest as training data, a modification unit configured to modify a reference value of the confidence, which is used to extract a region of interest, an extraction unit configured to extract the region of interest on the basis of the calculated confidence of each unit region and the modified reference value, and a display unit configured to display the extracted region of interest.

Abstract: A display control apparatus that performs rendering on volume data generated based on a signal obtained by receiving a photoacoustic wave generated by an object irradiated with light includes a first unit configured to obtain positional information of a surface of the object, a second unit configured to set a region inside the object between a surface located at a first distance from the surface of the object and a surface located at a second distance from the surface of the object as a display region on the basis of the positional information of the surface of the object, and a third unit configured to perform the rendering on the volume data in a manner that the display region and a region except for the display region can be discriminated from each other.

Abstract: The present disclosure provides a system and method for medical imaging. The method may include obtaining a preliminary image and scanning data of a subject acquired using a scanner. The method may also include determining a regularization parameter for a regularization item of an objective function based at least in part on the scanning data, wherein the regularization parameter includes at least two of a first component characterizing quality of the scanning data, a second component characterizing the scanner, or a third component characterizing a feature of the subject. The method may further include generating an image of the subject by reconstructing the preliminary image based on the objective function.

Abstract: A method is provided for image-processing an image dataset acquired from a patient by a medical imaging apparatus, (e.g., an X-ray apparatus), wherein the image dataset includes image values associated with image points, and depicts an acquisition region of the patient containing at least one object, (e.g., a medical device), to be enhanced, which is represented by image values within an image-value interval. The method includes determining a non-linearly high-pass filtered enhancement dataset, which is confined to an image portion containing image values lying in the image-value interval. The method also includes determining a result dataset by adding to the image dataset the enhancement dataset weighted by a weighting value. The method further includes outputting the result dataset.

Abstract: A route selection assistance system enabling easy selection of a route of a living body lumen for delivering a medical instrument to a site within a living body via the living body lumen, a recording medium on which a route selection assistance program is recorded, and a route selection assistance method are disclosed. The route selection assistance system includes: a receiving section configured to receive an input of site information specifying a target site; an image obtaining section configured to obtain image information on a living body of a target patient; a route extracting section configured to extract a plurality of routes of a living body lumen; a ranking assigning section configured to assign rankings to the plurality of routes according to ease of delivery of the medical instrument and patient scores determined according to magnitude of a burden imposed on the target patient.

Abstract: The most appropriate image for a diagnostic target among a plurality of images is selected and accurate diagnosis support information is presented regardless of the type of a selected image, a modality, or the like. An image diagnosis support apparatus includes: a diagnostic information generation unit that generates diagnostic information based on a plurality of medical images; a reliability calculation unit that evaluates an image quality and calculates an image reliability for each of the plurality of medical images; and a degree-of-contribution calculation unit that calculates a degree of contribution of each of the plurality of medical images to the diagnostic information using an internal parameter indicating a degree of appropriateness of each medical image for a diagnostic target and the reliability calculated by the reliability calculation unit. An image for detection used by the diagnostic information generation unit is generated based on the degree of contribution.

Abstract: There are provided a medical image processing device, and endoscope system, a diagnosis support method, and a program which can support diagnosis by avoiding an inappropriate report in a case where any of site information of an observation target and lesion type information detected from a medical image is incorrect. The medical image processing device includes at least one processor. The at least one processor acquires the medical image, acquires the site information indicating a site of an observation target included in the medical image, in a human body, detects a lesion from the medical image to acquire the lesion type information indicating a lesion type, determines presence or absence of a contradiction between the site information and the lesion type information, and decides a report mode of the site information and the lesion type information on the basis of a determination result.

Abstract: A system for PET image reconstruction is provided. The system may obtain PET data of a subject. The PET data may be associated with a plurality of coincidence events, which includes scattering events. The system may also generate a preliminary scatter sinogram relating to the scattering events based on the PET data. The system may also generate a target scatter sinogram relating to the scattering events by applying a scatter sinogram generator based on the preliminary scatter sinogram. The target scatter sinogram may have a higher image quality than the preliminary scatter sinogram. The system may further reconstruct a target PET image of the subject based on the PET data and the target scatter sinogram.

Abstract: A deep neural network for metal artifact reduction is described. A method for computed tomography (CT) metal artifact reduction (MAR) includes generating, by a projection completion circuitry, an intermediate CT image data based, at least in part, on input CT projection data. The intermediate CT image data is configured to include relatively fewer artifacts than an uncorrected CT image reconstructed from the input CT projection data. The method further includes generating, by an artificial neural network (ANN), CT output image data based, at least in part, on the intermediate CT image data. The CT output image data is configured to include relatively fewer artifacts compared to the intermediate CT image data. The method may further include generating, by detail image circuitry, detail CT image data based, at least in part, on input CT image data. The CT output image data is generated based, at least in part, on the detail CT image data.

Abstract: A method for determining the relative position between a first camera and a second camera used in a medical application, wherein the first camera captures a 2D image of a phantom, the second camera emits light onto the phantom and analyzes the reflected light, thus generating a 3D point cloud representing points on the surface of the phantom, and the phantom has a planar surface forming a background on which a plurality of 2D markers are formed, wherein one of the background and the 2D markers is reflective, thus reflecting light emitted by the second camera back to the second camera, and the other one is non-reflective, thus not reflecting light emitted by the second camera back to the second camera, the method involving that a) the first camera captures a 2D image of the phantom, b) the second camera generates a 3D point cloud representing the planar surface of the phantom, c) the 2D markers are identified in the 2D image, thus obtaining 2D marker data representing the locations of the 2D markers in the 2D

Abstract: An array device and a writing method thereof are provided. A synapse array device includes: a crossbar array, in which a resistive memory element is connected to each intersection of a plurality of row lines and a plurality of column lines; a row select/drive circuit selecting a row line of the crossbar array and applying a pulse signal to the selected row line; a column select/drive circuit selecting a column line of the crossbar array and applying a pulse signal to the selected column line; and a writing part writing to the resistive memory element connected to the selected row line and the selected column line. A first write voltage with controlled pulse width is applied to the selected row line, and a second write voltage with controlled pulse width is applied to the selected column line to perform set writing of the resistive memory element.

Abstract: A mechanism is provided in a data processing system for refining lesion contours with combined active contour and inpainting. The mechanism receives an initial segmented medical image having organ tissue including a set of object contours and a contour to be refined. The mechanism inpaints object voxels inside all contours of the set. The mechanism calculates an updated contour around the contour to be refined based on the in-painted object voxels to form an updated segmented medical image. The mechanism determines whether the updated segmented medical image is improved compared to the initial segmented medical image. The mechanism keeps the updated segmented medical image responsive to the updated segmented medical image being improved.

Abstract: In one embodiment, a method includes a computer system accessing a curvilinear image captured using a camera lens, generating multiple rectilinear images from the curvilinear image based at least in part on one or more calibration parameters associated with the camera lens, identifying semantic information in one or more of the rectilinear images by processing each of the multiple rectilinear images using a machine-learning model configured to identify semantic information in rectilinear images, and identifying semantic information in the curvilinear image based on the identified semantic information in the one or more rectilinear images.

Abstract: An automated method and system for determining the risk of developing a cancer in a subject, the method comprising preparing a tissue sample obtained from the subject for visually identifying at least one biological marker associated with the cancer, digitally scanning the prepared tissue sample, analyzing the scanned image of the tissue sample to identify regions of interest, quantifying at least one parameter associated with the marker, and executing an algorithm using the quantified parameter to calculate a risk score, wherein the risk score is representative of the risk of the individual developing the cancer.

Abstract: Provided is an artificial neural network circuit including unit weight memory cells including weight memory devices configured to store weight data and weight pass transistors, unit threshold memory cells including a threshold memory device programmed to store a threshold and a threshold pass transistor, a weight-threshold column in which the plurality of unit weight memory cells and the plurality of unit threshold memory cells are connected, and a sense amplifier configured to receive an output signal of the weight-threshold column as an input and receive a reference voltage as another input.

Abstract: This invention provides a signal-processing method that makes it possible to acquire, relatively easily and surely, a highly reliable normalized impulse-response signal without relying on the signal-correction processing after normalization. The signal-processing method of this invention includes a low-frequency extraction step, a high-frequency extraction step and a synthesizing step. In the low-frequency extraction step, only the low-frequency component is extracted from the spectrum of the first normalized signal NS1 obtained by normalizing the target signal Stgt in the time domain. In the high-frequency extraction step, only the high-frequency component is extracted from the spectrum of the second normalized signal NS2 obtained by normalizing the target signal Stgt in the frequency domain using the reference signal Sref.

Abstract: Various embodiments provide methods for configuring a phase-change random-access memory (PCRAM) structures, such as PCRAM operating in a single-level-cell (SLC) mode or a multi-level-cell (MLC) mode. Various embodiments may support a PCRAM structure being operating in a SLC mode for lower power and a MLC mode for lower variability. Various embodiments may support a PCRAM structure being operating in a SLC mode or a MLC mode based at least in part on an error tolerance for a neural network layer.

Abstract: The present application related to a method for detecting an object image using a convolutional neural network. Firstly, obtaining feature images by Convolution kernel, and then positioning an image of an object under detected by a default box and a boundary box from the feature image. By Comparing with the sample image, the detected object image is classifying to an esophageal cancer image or a non-esophageal cancer image. Thus, detecting an input image from the image capturing device by the convolutional neural network to judge if the input image is the esophageal cancer image for helping the doctor to interpret the detected object image.

Abstract: Various methods and systems are provided for artifact reduction with resolution preservation. In one example, a method includes obtaining projection data of an imaging subject, identifying a metal-containing region in the projection data, interpolating the metal-containing region to generate interpolated projection data, extracting high frequency content information from the projection data in the metal-containing region, adding the extracted high frequency content information to the interpolated projection data to generate adjusted projection data, and reconstructing one or more diagnostic images from the adjusted projection data.