Abstract: A method for training a learning-based medical scanner including (a) obtaining training data from demonstrations of scanning sequences, and (b) learning the medical scanner's control policies using deep reinforcement learning framework based on the training data.

Abstract: Machine learning is used to train a network to estimate a three-dimensional (3D) body surface and body regions of a patient from surface images of the patient. The estimated 3D body surface of the patient is used to determine an isocenter of the patient. The estimated body regions are used to generate heatmaps representing visible body region boundaries and unseen body region boundaries of the patient. The estimation of 3D body surfaces, the determined patient isocenter, and the estimated body region boundaries may assist in planning a medical scan, including automatic patient positioning.

Abstract: A device, structure, and method are provided whereby an insert layer is utilized to provide additional support for weaker and softer dielectric layer. The insert layer may be applied between two weaker dielectric layers or the insert layer may be used with a single layer of dielectric material. Once formed, trenches and vias are formed within the composite layers, and the insert layer will help to provide support that will limit or eliminate undesired bending or other structural motions that could hamper subsequent process steps, such as filling the trenches and vias with conductive material.

Abstract: A method of tube slot localization is provided using a tray coordinate system and a camera coordinate system. The method includes receiving, a series of images from at least one camera of a tray comprising tube slots arranged in a matrix of rows and columns. Each tube slot is configured to receive a sample tube. The method also includes automatically detecting fiducial markers disposed on cross sectional areas between the tube slots on the tray and receiving an encoder value indicating when each row of the tray is substantially at the center of the camera's field of view. The method further includes determining calibration information to provide mapping of locations from the tray coordinate system to locations from the camera coordinate system and automatically aligning the tray based on the encoder value and calibration information.

Abstract: Embodiments provide a method of using image-based tube top circle detection based on multiple candidate selection to localize the tube top circle region in input images. According to embodiments provided herein, the multi-candidate selection enhances the robustness of tube circle detection by making use of multiple views of the same tube to improve the robustness of tube top circle detection. With multiple candidates extracted from images under different viewpoints of the same tube, the multi-candidate selection algorithm selects an optimal combination among the candidates and provides more precise measurement of tube characteristics. This information is invaluable in an IVD environment in which a sample handler is processing the tubes and moving the tubes to analyzers for testing and analysis.

Abstract: An automation method is disclosed for an X-ray tube scanner having an X-ray tube and an X-ray detector. The method allows the X-ray tube scanner to detect the X-ray detector's plane with an object to be imaged placed on the X-ray detector; determine a boundary box of the object to be imaged on the X-ray detector; determine the object's center position and orientation on the X-ray detector's plane; transfer the object's center position from the object's coordinate system to the X-ray tube's coordinate system; and estimate the X-ray tube control parameters for aligning the X-ray field emitted from the X-ray tube's collimator to the object's center position and the object's orientation on the X-ray detector.

Abstract: A resistance sensing apparatus for exercise equipment includes a resistance adjusting assembly and a sensing unit. The resistance adjusting assembly includes an adjusting unit, a tubular member disposed above the adjusting unit, and an adjusting shaft mounted in the tubular member. The adjusting shaft has a first threaded portion and a second threaded portion formed thereon. The adjusting unit is threaded onto the first threaded portion. The sensing unit includes a second threaded member threadedly engaged to the second threaded portion, a first sensing member is disposed on one of the adjusting unit and the second threaded member, the second sensing member is disposed on the other of the adjusting unit and the second threaded member. By adjusting the adjusting unit and the second threaded member, a distance of the first and the second sensing member is changed and generates corresponding signals.

Abstract: A lateral glide elliptical exercise apparatus includes a frame defining a center line, a pair of pedal units disposed at two opposite lateral sides relative to the center line each including a pivoting block and a pedal shaft pivotally connected to the pivoting block, a damping unit for providing a damping resistance to the pedal units, and a pair of gliding guide units respectively mounted at the frame, each gliding guide unit includes a gliding guide, an actuation block and a linkage arranged so that the actuation block can be driven by the associating linkage to slide smoothly between an inner end portion and an outer end portion of the associating gliding guide when the pedal units are being alternately pedaled by the user.

Abstract: Methods for image-based detection of the tops of sample tubes used in an automated diagnostic analysis system may be based on a convolutional neural network to pre-process images of the sample tube tops to intensify the tube top circle edges while suppressing the edge response from other objects that may appear in the image. Edge maps generated by the methods may be used for various image-based sample tube analyses, categorizations, and/or characterizations of the sample tubes to control a robot in relationship to the sample tubes. Image processing and control apparatus configured to carry out the methods are also described, as are other aspects.

Abstract: A method of characterizing a serum and plasma portion of a specimen in regions occluded by one or more labels. The characterization may be used for Hemolysis, Icterus, and/or Lipemia, or Normal detection. The method captures one or more images of a labeled specimen container including a serum or plasma portion, processes the one or more images to provide segmentation data and identification of a label-containing region, and classifying the label-containing region with a convolutional neural network (CNN) to provide a pixel-by-pixel (or patch-by-patch) characterization of the label thickness count, which may be used to adjust intensities of regions of a serum or plasma portion having label occlusion. Optionally, the CNN can characterize the label-containing region as one of multiple pre-defined label configurations. Quality check modules and specimen testing apparatus adapted to carry out the method are described, as are other aspects.

Abstract: A method of characterizing a serum and plasma portion of a specimen in regions occluded by one or more labels. The characterization method may be used to provide input to an HILN (H, I, and/or L, or N) detection method. The characterization method includes capturing one or more images of a labeled specimen container including a serum or plasma portion from multiple viewpoints, processing the one or more images to provide segmentation data including identification of a label-containing region, determining a closest label match of the label-containing region to a reference label configuration selected from a reference label configuration database, and generating a combined representation based on the segmentation information and the closest label match. Using the combined representation allows for compensation of the light blocking effects of the label-containing region. Quality check modules and testing apparatus and adapted to carry out the method are described, as are other aspects.

Abstract: A method of characterizing a serum and plasma portion of a specimen in regions occluded by one or more labels. The characterization may be used for determining Hemolysis (H), Icterus (I), and/or Lipemia (L), or Normal (N) of a serum or plasma portion of a specimen. The method includes capturing one or more images of a labeled specimen container including a serum or plasma portion, processing the one or more images with a convolutional neural network to provide a determination of Hemolysis (H), Icterus (I), and/or Lipemia (L), or Normal (N). In further embodiments, the convolutional neural network can provide N-Class segmentation information. Quality check modules and testing apparatus adapted to carry out the method are described, as are other aspects.

Abstract: A method of decoding a bitstream by an electronic device is provided. An image frame is received from the bitstream, and a block unit is determined from the image frame. A prediction index of the block unit is determined from the bitstream. A plurality of reference mode indices is determined based on a plurality of neighboring blocks of the block unit. The electronic device determines whether the reference mode indices are greater than a specific one of a plurality of non-angular mode indices. When the reference mode indices are greater than the specific non-angular mode index, the electronic device determines whether a difference between the reference mode indices is equal to two. When the difference is equal to two, a prediction mode is selected according to the prediction index and based on a first candidate list. Then, the block unit is reconstructed based on the prediction mode.

Abstract: Embodiments include a medical imaging device and a method controlling one or more parameters of a medical imaging device. In one embodiment, a method includes receiving image data representing a first image of an object to be imaged using the radiation source and detecting a plurality of positions of respective predetermined features in the first image. Based upon the detected positions, a boundary of an imaging area of the object to be imaged is determined. Based on the determined boundary, one or more parameters of the radiation source unit are controlled.

Abstract: A method of decoding a bitstream by an electronic device is provided. A block unit is determined from an image frame according to the bitstream. One of a plurality of candidate groups is selected based on a set flag in the bitstream. A plurality of merge mode with motion vector difference (MMVD) indications of the block unit is determined according to the bitstream. A plurality of MMVD prediction parameters of the block unit is determined based on the plurality of MMVD indications and the selected candidate group. The block unit is reconstructed based on the plurality of MMVD prediction parameters.

Abstract: A perpendicularly magnetized spin-orbit magnetic device including a heavy metal layer, a magnetic tunnel junction, a first antiferromagnetic layer, a first block layer and a first stray field applying layer is provided. The magnetic tunnel junction is disposed on the heavy metal layer. The first block layer is disposed between the magnetic tunnel junction and the first antiferromagnetic layer. The first stray field applying layer is disposed between the first antiferromagnetic layer and the first block layer. The magnetic tunnel junction comprises a free layer, a tunneling barrier layer, and pinned layer. The tunneling barrier layer is disposed on the free layer. The pinned layer is disposed on the tunneling barrier layer. A film plane area of the free layer is greater than a film plane area of the tunneling barrier layer and a film plane area of the pinned layer.

Abstract: A perpendicularly magnetized spin-orbit magnetic device including a heavy metal layer, a magnetic tunnel junction, a first antiferromagnetic layer, a first block layer and a first stray field applying layer is provided. The magnetic tunnel junction is disposed on the heavy metal layer. The first block layer is disposed between the magnetic tunnel junction and the first antiferromagnetic layer. The first stray field applying layer is disposed between the first antiferromagnetic layer and the first block layer. The first stray field applying layer provides a stray magnetic field parallel to a film plane. The first antiferromagnetic layer contacts the first stray field applying layer to define the direction of the magnetic moment in the first stray field applying layer.

Abstract: A method of decoding a bitstream by an electronic device is provided. A block unit is determined from an image frame according to the bitstream. A sub-partition direction of the block unit is determined from a plurality of candidate directions according to the bitstream, and a prediction mode of the block unit is determined from a plurality of candidate mode according to the bitstream. The block unit is partitioned along the sub-partition direction to generate a plurality of sub-block units. A plurality of sample sets each including a plurality of reference samples is determined for the sub-block units and different from each other. Each of the plurality of sub-block units is reconstructed based on a corresponding one of the sample sets according to the prediction mode of the block unit.

Abstract: A method of decoding a bitstream by an electronic device is provided. A block unit having a block size is determined from an image frame according to the bitstream. The number of one or more reference lines neighboring to the block unit is determined based on the block size. One of the one or more reference lines is selected based on the number of the one or more reference lines. The block unit is reconstructed based on the selected one of the one or more reference lines.

Abstract: A system includes: a movable X-ray tube scanner; a range sensor movable with the X-ray tube scanner; an X-ray detector positioned to detect X-rays from the X-ray tube passing through a standing subject between the X-ray tube and the X-ray detector; and a processor configured for automatically controlling the X-ray tube scanner to transmit X-rays to a region of interest of the patient while the subject is standing between the X-ray tube and the X-ray detector.