Abstract: A 3D memory device may include a first set of memory layers, a second set of memory layers above the first set of memory layers, and a first dummy memory layer between the first and second memory layers. The 3D memory device may include a plurality of NAND memory strings each extending through the first and second set of memory layers and the first dummy memory layer. The 3D memory device may include a word line (WL) driving circuit that, when programming one of the first set of memory layers, may be configured to apply a second pre-charge voltage to the first dummy memory layer during the pre-charge period. The second pre-charge voltage may overlap with the first pre-charge voltage and ramp down prior to the first pre-charge voltage.

Abstract: Embodiments discussed herein facilitate segmentation of vascular plaque, training a deep learning model to segment vascular plaque, and/or informing clinical decision-making based on segmented vascular plaque. One example embodiment accessing vascular imaging data for a patient, wherein the vascular imaging data comprises a volume of interest; pre-process the vascular imaging data to generate pre-processed vascular imaging data; provide the pre-processed vascular imaging data to a deep learning model trained to segment a lumen and a vascular plaque; and obtain segmented vascular imaging data from the deep learning model, wherein the segmented vascular imaging data comprises a segmented lumen and a segmented vascular plaque in the volume of interest.

Abstract: Various methods and systems are provided for ultrasound imaging. In one embodiment, a method comprises acquiring, with an ultrasound transducer of a scanning apparatus during an ultrasound scan of a patient, an ultrasound image, detecting, with an artificial intelligence model, a region of interest within the ultrasound image including a possible tumor, acquiring, with the ultrasound transducer, an elastic image of tissue within the region of interest, and displaying, with a display device, the elastic image. In this way, shear wave elastography may be automatically targeted to a region of interest, thereby reducing the processing load for the analysis and enabling a higher elasticity imaging frame rate for three-dimensional ultrasound imaging.

Abstract: An inverse visualization of a time-resolved angiographic image data set of a vascular system of a patient that was recorded by a medical imager during the flow of a contrast medium through the vascular system is provided. The time-resolved angiographic image data set of the vascular system has a temporal sequence of frames of the vascular system corresponding to the contrast medium filling process. A data set from bolus arrival times for each pixel or voxel is determined. The bolus arrival time corresponds to the time in the temporal sequence at which a predetermined contrast enhancement due to the contrast medium filling first occurs. A data set of temporally inverted bolus arrival times with respect to the contrast medium filling is determined for each pixel or voxel, resulting in a temporally inverted sequence of frames with respect to the contrast medium filling. The time-resolved angiographic image data set in the temporally inverted sequence is visualized.

Abstract: According to one embodiment, a medical data processing apparatus includes processing circuitry. The processing circuitry acquires medical data, and generates an imaging parameter by inputting the medical data to a trained model, the imaging parameter being a parameter of a medical image diagnostic apparatus with respect to the medical data, the trained model being trained to generate an imaging parameter of the medical image diagnostic apparatus based on medical data.

Abstract: Methods of processing images, such as ultrasound images, to determine integrity of an implant are described. The method may include receiving an ultrasound image of an implant in a body of a subject; determining one or more characteristics of a surface of the implant based on an intensity of pixels of the ultrasound image; generating a predicted status of the implant based on the one or more characteristics by comparison of the one or more characteristics with a database of image data; and displaying the predicted status of the implant. The implant may be a breast implant, for example, wherein the method is useful for analyzing the presence or probability of extracapsular ruptures, contractures, and combinations thereof.

Abstract: Described are memory modules that support different error detection and correction (EDC) schemes in both single- and multiple-module memory systems. The memory modules are width configurable and support the different EDC schemes for relatively wide and narrow module data widths. Data buffers on the modules support the half-width and full-width modes, and also support time-division-multiplexing to access additional memory components on each module in support of enhanced EDC.

Abstract: A virtual conference in relation to diagnostic object data is created. Messages posted to the virtual conference from terminal devices of users participating in the virtual conference are received, and the posted messages are sent to the other terminal devices beside the terminal devices of the users. Information relating to the diagnostic object data is generated, which information is obtained in accordance with analysis results of analyzing the posted messages. The information relating to the diagnostic object data is sent to the terminal devices.

Abstract: A method for performing a computer-aided diagnosis (CAD) includes: acquiring a medical image set; generating a three-dimensional (3D) tumor distance map corresponding to the medical image set, each voxel of the tumor distance map representing a distance from the voxel to a nearest boundary of a primary tumor present in the medical image set; and performing neural-network processing of the medical image set to generate a predicted probability map to predict presence and locations of oncology significant lymph nodes (OSLNs) in the medical image set, wherein voxels in the medical image set are stratified and processed according to the tumor distance map.

Abstract: The present disclosure includes apparatuses, methods, and systems for increase of a sense current in memory. An embodiment includes a memory having a plurality of memory cells, and circuitry configured to count a number of program operations performed on the memory cells of the memory during operation of the memory, and increase a magnitude of a current used to sense a data state of the memory cells of the memory upon the count of the number of program operations reaching a threshold count.

Abstract: The present disclosure includes apparatuses and methods for programming memory cells using asymmetric current pulses. An embodiment includes a memory having a plurality of self-selecting memory cells, and circuitry configured to program a self-selecting memory cell of the memory by applying a first current pulse or a second current pulse to the self-selecting memory cell, wherein the first current pulse is applied for a longer amount of time than the second current pulse and the first current pulse has a lower amplitude than the second current pulse.

Abstract: A Method, apparatus, device, and storage media for image processing are provided. The method include: acquiring a set of image sequences, the set of image sequences including a plurality of image sequences; determining a first similarity measurement between image sequences in the set of image sequences; dividing the set of image sequences into one or more subset of image sequences based on a first similarity measurement; and determining, in each subset of image sequences, degrees of correlation between images in one image sequence of the subset of image sequences and images in other image sequences of the subset of image sequences.

Abstract: Methods, systems, and devices for a modified write voltage for memory devices are described. In an example, the memory device may determine a first set of memory cells to be switched from a first logic state (e.g., a SET state) to a second logic state (e.g., a RESET state) based on a received write command. The memory device may perform a read operation to determine a subset of the first set of memory cells (e.g., a second set of memory cells) having a conductance threshold satisfying a criteria based on a predicted drift of the memory cells. The memory device may apply a RESET pulse to each of the memory cells within the first set of memory cells, where the RESET pulse applied to the second set of memory cells is modified to decrease voltage threshold drift in the RESET state.

Abstract: Disclosed herein are systems and methods for providing interactive graphical user interfaces (GUIs) for users, such as medical professionals, to glean insight about connectivity data associated with a particular brain. A method can include overlaying nodes representing locations of parcels of a patient's brain on a representation of a brain and displaying the representation of the brain with the overlaid nodes in a GUI. Nodes having connectivity above a first threshold can be represented in a first indicia and nodes having connectivity below a second threshold can be represented in a second indicia. The method can include receiving user input and taking an action based on the user input. The user input can include selecting an area of the representation of the brain for excision. Taking an action based on the input can include calculating an impact of excising the area of the brain on the particular patient.

Abstract: In one embodiment, a semiconductor storage device includes a plurality of memory chips, at least one of the memory chips including a first controller configured to be shifted to a wait state of generating a peak current, before generating the peak current in accordance with a command. The device further includes a control chip including a second controller configured to search a state of the first controller and control, based on a result of searching the state of the first controller, whether or not to issue a cancel instruction for the wait state to the first controller that has been shifted to the wait state.

Abstract: Examples of the present disclosure describe systems and methods for predicting the reading time and/or reading complexity of a breast image. In aspects, a first set of data relating to the reading time of breast images may be collected from one or more data sources, such as image acquisition workstations, image review workstations, and healthcare professional profile data. The first set of data may be used to train a predictive model to predict/estimate an expected reading time and/or an expected reading complexity for various breast images. Subsequently, a second set of data comprising at least one breast image may be provided as input to the trained predictive model. The trained predictive model may output an estimated reading time and/or reading complexity for the breast image. The output of the trained predictive model may be used to prioritize mammographic studies or optimize the utilization of available time for radiologists.

Abstract: An imaging system includes a microscope to generate magnified images of regions of interest of a tissue sample, a camera to capture and store the magnified images, and a controller. The controller is configured to, for each magnification level in a sequence of increasing magnification levels, image one or more regions of interest of the tissue sample at the current magnification level. For each region of interest, data is generated defining one or more refined regions of interest based on the magnified image of the region of interest of the tissue sample at the current magnification level. Each refined region of interest corresponds to a proper subset of the tissue sample, and the refined regions of interest of the tissue sample provide the regions of interest to be imaged at a next magnification level from the sequence of increasing magnification levels.

Abstract: A method is for operating a nonvolatile dual in-line memory module (NVDIMM). The NVDIMM includes a dynamic random access memory (DRAM) and a nonvolatile memory (NVM) device, the DRAM including a first input/output (I/O) port and a second I/O port, and the second I/O port connected to the NVM device. The method includes receiving an externally supplied command signal denoting a read/write command and a transfer mode, driving a multiplexer to select at least one of the first and second I/O ports according to the transfer mode of the command signal, and reading or writing data according to the read/write command of the command signal in at least one of the DRAM and NVM device using the at least one of the first and second I/O ports selected by driving the multiplexer.

Abstract: The disclosure relates to a method and a system for hand pose recognition, a device and a storage medium are disclosed in embodiments of the disclosure. The method includes: capturing a RGB image of a hand from a RGB camera and capturing a depth image of the hand from an active depth camera, so as to obtain a hand pose data set according to the RGB image and the depth image; processing the hand pose data set to obtain a 3D joint position, and taking the 3D joint position as a data set for training a software model; extracting the RGB image by a feature extractor based on a depth neural network to obtain a feature map of a hand pose; and processing the feature map according to an attention mechanism to obtain a global feature map of the hand pose.

Abstract: Computer-implemented methods and systems are provided for interpreting a whole-slide image of a tissue specimen. Such a method includes detecting biological entities in a region of interest independently at each magnification level in a whole-slide image. An entity graph is generated for each magnification level, the entity graph comprising nodes, representing respective biological entities detected at that magnification level, interconnected by edges representing interactions between entities. The method also includes, for each region of interest, generating a hierarchical graph, defining a hierarchy of the entity graphs for that region, in which nodes of different entity graphs are interconnected by hierarchical edges representing hierarchical relations between nodes of the entity graphs.