Abstract: The present disclosure belongs to the field of radio frequency circuit design, and in particular relates to a M×N millimeter wave and terahertz planar dipole end-fire array antenna. The M×N millimeter wave and terahertz planar dipole end-fire array antenna is composed of M paths of N× end-fire linear array antennas arranged at equal intervals, and the distance d between two adjacent N× end-fire linear array antennas is less than ?, where ? is the wavelength, and both M and N are integers greater than 1. By connecting linear type feed networks of the M paths of N× end-fire linear array antennas to M-path in-phase radio frequency signal transmitter and controlling the distance between two adjacent N× end-fire linear array antennas to be less than the effective wavelength, a higher gain and a higher half-power width can be realized, and the power consumption of the transmitter can be reduced.

Abstract: A non-transitory computer readable medium storing instructions readable and executable by an imaging workstation (14) including at least one electronic processor (16) to perform a dataset generation method (100) operating on emission imaging data acquired of a patient for one or more axial frames at a corresponding one or more bed positions, the method comprising: (a) identifying a frame of interest from the one or more axial frames; (b) generating simulated lesion data by simulating emission imaging data for the frame of interest of at least one simulated lesion placed in the frame of interest; (c) generating simulated frame emission imaging data by simulating emission imaging data for the frame of interest of the patient; (d) determining a normalization factor comprising a ratio of the value of a quantitative metric for the simulated patient data and the value of the quantitative metric for the emission imaging data acquired of the same patient for the frame of interest; and (e) generating a hybrid data set

Abstract: A non-transitory computer-readable medium stores instructions readable and executable by at least one electronic processor (181, 182, 20) to perform an imaging method (100). The method includes: reconstructing emission imaging data to generate an emission image of a lesion; converting intensity values of the emission image to at least one standardized uptake value (SUV value) for the lesion; processing input data using a regression neural network (NN) (28) to output an SUV correction factor for the lesion, wherein the input data includes at least two of (i) image data comprising the emission image or a feature vector representing the emission image, (ii) the at least one SUV value, (iii) a size of the lesion, and (iv) reconstruction parameters used in the reconstructing; and controlling a display device (24) to display at least one of (I) the SUV correction factor and (II) a corrected SUV value generated by applying the SUV correction factor to the at least one SUV value.

Abstract: A non-transitory computer-readable medium stores instructions readable and executable by a workstation (18) including at least one electronic processor (20) to perform an image reconstruction method (100).

Abstract: A non-transitory computer readable medium storing instructions readable and executable by an imaging workstation (14) including at least one electronic processor (16) to perform a dataset generation method (100) operating on emission imaging data acquired of a patient for one or more axial frames at a corresponding one or more bed positions, the method comprising: (a) identifying a frame of interest from the one or more axial frames; (b) generating simulated lesion data by simulating emission imaging data for the frame of interest of at least one simulated lesion placed in the frame of interest; (c) generating simulated frame emission imaging data by simulating emission imaging data for the frame of interest of the patient; (d) determining a normalization factor comprising a ratio of the value of a quantitative metric for the simulated patient data and the value of the quantitative metric for the emission imaging data acquired of the same patient for the frame of interest; and (e) generating a hybrid data set

Abstract: An imaging apparatus includes a nuclear medicine imaging device (10), a patient table (14), and a table controller (18) comprising an electronic processor and actuators configured to position the patient table along an axial direction and in a transverse plane that is transverse to the axial direction. An automatic positioning engine (40) comprises an electronic processor (42) programmed to determine an optimal position of the patient table in the transverse plane for imaging a target of interest in a patient based on a prior image (20, 34) of the patient. The table controller operates the patient table to position the patient table in accord with the determined optimal position of the patient table.

Abstract: Provided is a method for plant genome site-directed modification. Specifically, a method for plant genome site-directed modification introduced by RNA is provided. By utilizing nucleic acid construct with particular structure, site-directed modification may be performed at pre-determined site in plant genome with high efficiency. Useful for screening plant with improved traits efficiently.