Abstract: A method for generating and evaluating N-to-1 mappings, between spatial point sets in nD, n=2 or 3 implemented on a computing device comprising a programmable general purpose processor and a programmable data-parallel coprocessor and a memory coupled with them. Embodiments comprises using the computing device to receive a first and a second spatial point sets, the first spatial point set comprising a first non-empty portion of non-isolated points and a second non-empty portion of constrained points, an array of fixed correspondents for the second non-empty portion, and a CCISS or padded CCISS between the first non-isolated portion and the second spatial point set, and use these to generate an array of N-to-1 mappings between the first portion of non-isolated points and the second spatial point set, an array of overall distance measures for the array of N-to-1 mappings, and an optimal N-to-1 mapping with the lowest overall distance measure.

Abstract: A resistive memory apparatus including bit lines, word lines, a memory array, bypass paths, select circuits, and a switch circuit is provided. The word lines are respectively crossed with the bit lines. The memory array includes memory elements. One end of each of the memory elements is coupled to the corresponding word line, and another end of each of the memory elements is coupled between a first node and a second node on the corresponding bit line. Each of the bypass paths is connected in parallel with the corresponding bit line between the first node point and the second node. Each of the select circuits is coupled to the corresponding bit line and bypass path, and configured to select the coupled bit line or bypass path. The switch circuit is coupled to the word lines, and configured to select one of the word lines.

Abstract: Devices, systems and methods for adaptively controlling a reset current of a memory cell are described. A system comprises: a mirror circuit with one branch coupled with a top electrode of the memory cell and the other branch coupled with one end of a resistive reference, and wherein a bottom electrode of the memory cell is coupled to a reference potential, the other end of the resistive reference is provided with a first electric potential; a control circuit; and a feedback circuit for feeding an electric potential to the top electrode of the memory cell.

Abstract: In an embodiment, a memory controller in an integrated circuit may generate refreshes for one or more DRAMs coupled to the integrated circuit according to a refresh rate. The integrated circuit may include one or more temperature sensors. A rate of change of the temperature may be determined from the temperature sensors. If the rate is greater than a threshold, the memory controller may generate refreshes according to a refresh rate specified by the DRAMs. If the rate is less than the threshold, the memory controller may generate refreshes at a reduced refresh rate.

Abstract: Disclosed is a CT image generation method for attenuation correction of PET images. According to the method, a CT image and a PET image at T1 and a PET image at T2 are acquired and input into a trained deep learning network to obtain a CT image at T2; the CT image can be applied to the attenuation correction of the PET image, thereby obtaining more an accurate PET AC (Attenuation Correction) image. According to the CT image generation method for attenuation correction of PET images, the dosage of X-rays received by a patient in the whole image acquisition stage can be reduced, and physiological and psychological pressure of the patient is relieved. In addition, the later image acquisition only needs a PET imaging device, without the need of PET/CT device, cost of imaging resource distribution can be reduced, and the imaging expense of the whole stage is reduced.

Abstract: A method including receiving, from a C-arm device, a plurality of fluoroscopic images of a lung, wherein each fluoroscopic image is obtained with the C-arm device positioned at a particular pose of a plurality of poses traversed by the C-arm device while the C-arm device is moved through a range of motion including a range of rotation, the range of rotation encompassing a sweep angle between 45 degrees and 120 degrees; generating an enhanced tomographic image of the lung, by utilizing: a trained machine learning model and the plurality of fluoroscopic images; and outputting a representation of the enhanced tomographic image, wherein, when tested by a method in which: the lung includes a lesion smaller than 30 millimeters, and the representation is an axial slice showing a boundary of the lesion, the lesion has a contrast-to-noise value of at least 5 as compared to a background of the representation.

Abstract: A phase-change memory (10) for the non-volatile storage of binary contents stores the binary contents electrically and/or optically in a non-volatile manner by locally switching a material (18) between an amorphous and a crystalline phase. The state with respect to the electrical conductivity of the material (18) and/or the reflection properties of the material (18) determines the information content of the phase-change memory (10). A method for non-volatile storage of binary contents in a phase-change memory (10), which stores the binary contents electrically and/or optically in a non-volatile manner by locally switching a material (18) between an amorphous and a crystalline phase, whereby the state with respect to the electrical conductivity of the material (18) and/or the reflection properties of the material (18) determines the information content of the phase-change memory (10).

Abstract: Embodiments relate to an image processing circuit comprising a noise reduction circuit configurable to perform bilateral filtering on demosaiced and resampled image data, or on raw image data, based on the operating mode of the image processing circuit. The noise reduction circuit filters received image data based upon directional taps, by selecting, for each pixel, a set of neighbor pixels, and comparing values of the set of neighbor pixels to determine whether the pixel lies on a directional edge. For raw images, the noise reduction circuit selects the set of neighbor pixels to include a plurality of pixels of the same color channel as the pixel, and one or more additional pixels of a different color channel, where color values for the one or more additional pixels are determined by interpolating color values of two or more adjacent pixels of the same color channel as the pixel.

Abstract: According to an embodiment, a phase-change memory device comprises: an upper electrode and a lower electrode; a phase-change layer in which a crystal state thereof is changed by heat supplied by the upper electrode and the lower electrode; and a selector which selectively switches the heat supplied by the upper electrode and the lower electrode to the phase-change layer, wherein the selector is formed of a compound which includes a transition metal in the phase-change material so as to have a high resistance when the crystalline state of the selector is crystalline and so as to have a low resistance when the crystalline state of the selector is non-crystalline.

Abstract: Resistive memory devices are provided which are configured to mitigate resistance drift. A device comprises a phase-change element, a resistive liner, a first electrode, a second electrode, and a third electrode. The resistive liner is disposed in contact with a first surface of the phase-change element. The first electrode is coupled to a first end portion of the resistive liner. The second electrode is coupled to a second end portion of the resistive liner. The third electrode is coupled to the first surface of the phase-change element.

Abstract: A deep learning (DL) convolution neural network (CNN) reduces noise in positron emission tomography (PET) images, and is trained using a range of noise levels for the low-quality images having high noise in the training dataset to produce uniform high-quality images having low noise, independently of the noise level of the input image. The DL-CNN network can be implemented by slicing a three-dimensional (3D) PET image into 2D slices along transaxial, coronal, and sagittal planes, using three separate 2D CNN networks for each respective plane, and averaging the outputs from these three separate 2D CNN networks. Feature-oriented training can be implemented by segmenting each training image into lesion and background regions, and, in the loss function, applying greater weights to voxels in the lesion region. Other medical images (e.g. MRI and CT) can be used to enhance resolution of the PET images and provide partial volume corrections.

Abstract: Provided herein may be a resistive memory device and a method of operating the resistive memory device. The resistive memory device may include strings coupled between one or more source lines and one or more bit lines, each string including a set of one or more resistive memory cells, one or more word lines respectively coupled to the set of one or more resistive memory cells; and a voltage generator configured to control a level of a turn-on voltage to be applied to one or more unselected word lines among the one or more word lines depending on a program target state of a subset of resistive memory cells including one or more resistive memory cells selected from among the set of one or more resistive memory cells.

Abstract: Methods, systems, and devices for a refresh operation of a memory cell are described. A memory device may include a plurality of rows of memory cells. Each row of memory cells may undergo a quantity of access operations (e.g., read operations, write operations). During a read operation, a logic state of one or more memory cells may be determined by applying a read pulse having a first polarity. Based on the one or more memory cells storing a particular logic state (e.g., a first logic state), a refresh operation may be performed. During a refresh operation, a refresh pulse having a second polarity (e.g., a different polarity than the first polarity) may be applied to the one or more memory cells.

Abstract: A method for programming a phase change memory including a first layer of a phase change material capable of switching between a crystalline and an amorphous state and vice versa, the method including applying a programming current through the first layer so that an evolution of the areal density of this current as a function of time t decreases from a first level, between a first time and a second time, following a first evolution in time respecting, or being close to J 0 ? ( t ) = K t where K is a constant.

Abstract: A deep learning (DL) convolution neural network (CNN) reduces noise in positron emission tomography (PET) images, and is trained using a range of noise levels for the low-quality images having high noise in the training dataset to produceuniform high-quality images having low noise, independently of the noise level of the input image. The DL-CNN network can be implemented by slicing a three-dimensional (3D) PET image into 2D slices along transaxial, coronal, and sagittal planes, using three separate 2D CNN networks for each respective plane, and averaging the outputs from these three separate 2D CNN networks. Feature-oriented training can be implemented by segmenting each training image into lesion and background regions, and, in the loss function, applying greater weights to voxels in the lesion region. Other medical images (e.g. MRI and CT) can be used to enhance resolution of the PET images and provide partial volume corrections.

Abstract: Methods, systems, and devices for decoding for a memory device are described. A decoder of a memory device may include transistors in a first layer between a memory array and a second layer that includes one or more components associated with the memory array. The second layer may include CMOS pre-decoding circuitry, among other components. The decoder may include CMOS transistors in the first layer. The CMOS transistors may control which voltage source is coupled with an access line based on a gate voltage applied to a p-type transistor and a n-type transistor. For example, a first gate voltage applied to a p-type transistor may couple a source node with the access line and bias the access line to a source voltage. A second gate voltage applied to the n-type transistor may couple a ground node with the access line and bias the access line to a ground voltage.

Abstract: A method for setting memory elements in a plurality of states includes applying a set signal to a memory element to transition the memory element from a low-current state to a high-current state; applying a partial reset signal to the memory element to transition the memory element from the high-current state to a state between the high-current state and the low-current state; determining whether the state corresponds to a predetermined state; and applying one or more additional partial reset signals to the memory element until the state corresponds to the predetermined current state. The memory element may be coupled in series with a transistor, and a voltage control circuit may apply voltages to the transistor to set and partially reset the memory element.

Abstract: A nonvolatile memory device includes a differential current driver that receives a first differential signal and a second differential signal, which are based on a temperature, and generates a first compensation current and a second compensation current corresponding to a difference value between the first and second differential signals. A current mirror circuit copies a first current, which is a sum of a reference current and the first compensation current, to generate a second current having a same value as a value of the first current and regulates the reference current depending on a difference value of the second current and the second compensation current. A trimming circuit generates a program current or a read current based on the regulated reference current.

Abstract: Apparatus and methods are described for use with a bodily emission of a subject that is disposed within a toilet bowl. While the bodily emission is disposed within the toilet bowl, light is received from the toilet bowl using one or more light sensors. Using a computer processor, intensities of at least two spectral bands that are within a range of 530 nm to 785 nm are determined, by analyzing the received light, and a ratio of the intensities of the two spectral bands is determined. In response thereto, the computer processor determines that there is a presence of blood within the bodily emission. The computer processor generates an output on an output device, at least partially in response thereto. Other applications are also described.

Abstract: A computing system includes a processor and a non-transitory, computer-readable medium including instructions that, when executed by the processor, causes the computing system to receive a machine data set; process the machine data set using a trained machine-learned model to generate predicted variety profile index values, and transmit the variety profile index values to a client computing device. A computer-implemented method includes receiving a machine data set; processing the machine data set using a trained machine-learned model to generate predicted variety profile index values, and transmitting the variety profile index values to a client computing device.