1,115 research outputs found
A Novel Deep Learning Framework for Internal Gross Target Volume Definition from 4D Computed Tomography of Lung Cancer Patients
In this paper, we study the reliability of a novel deep learning framework for internal gross target volume (IGTV) delineation from four-dimensional computed tomography (4DCT), which is applied to patients with lung cancer treated by Stereotactic Body Radiation Therapy (SBRT). 77 patients who underwent SBRT followed by 4DCT scans were incorporated in a retrospective study. The IGTV_DL was delineated using a novel deep machine learning algorithm with a linear exhaustive optimal combination framework, for the purpose of comparison, three other IGTVs base on common methods was also delineated, we compared the relative volume difference (RVI), matching index (MI) and encompassment index (EI) for the above IGTVs. Then, multiple parameter regression analysis assesses the tumor volume and motion range as clinical influencing factors in the MI variation. Experimental results demonstrated that the deep learning algorithm with linear exhaustive optimal combination framework has a higher probability of achieving optimal MI compared with other currently widely used methods. For patients after simple breathing training by keeping the respiratory frequency in 10 BMP, the four phase combinations of 0%, 30%, 50% and 90% can be considered as a potential candidate for an optimal combination to synthesis IGTV in all respiration amplitudes
Robust Sum-Rate Maximization in Transmissive RMS Transceiver-Enabled SWIPT Networks
In this paper, we propose a state-of-the-art downlink communication
transceiver design for transmissive reconfigurable metasurface (RMS)-enabled
simultaneous wireless information and power transfer (SWIPT) networks.
Specifically, a feed antenna is deployed in the transmissive RMS-based
transceiver, which can be used to implement beamforming. According to the
relationship between wavelength and propagation distance, the spatial
propagation models of plane and spherical waves are built. Then, in the case of
imperfect channel state information (CSI), we formulate a robust system
sum-rate maximization problem that jointly optimizes RMS transmissive
coefficient, transmit power allocation, and power splitting ratio design while
taking account of the non-linear energy harvesting model and outage probability
criterion. Since the coupling of optimization variables, the whole optimization
problem is non-convex and cannot be solved directly. Therefore, the alternating
optimization (AO) framework is implemented to decompose the non-convex original
problem. In detail, the whole problem is divided into three sub-problems to
solve. For the non-convexity of the objective function, successive convex
approximation (SCA) is used to transform it, and penalty function method and
difference-of-convex (DC) programming are applied to deal with the non-convex
constraints. Finally, we alternately solve the three sub-problems until the
entire optimization problem converges. Numerical results show that our proposed
algorithm has convergence and better performance than other benchmark
algorithms
Direct observation of ideal electromagnetic fluids
Near-zero-index (NZI) media have been theoretically identified as media where electromagnetic radiations behave like ideal electromagnetic fluids. Within NZI media, the electromagnetic power flow obeys equations similar to those of motion for the velocity field in an ideal fluid, so that optical turbulence is intrinsically inhibited. Here, we experimentally observe the electromagnetic power flow distribution of such an ideal electromagnetic fluid propagating within a cutoff waveguide by a semi-analytical reconstruction technique. This technique provides direct proof of the inhibition of electromagnetic vorticity at the NZI frequency, even in the presence of complex obstacles and topological changes in the waveguide. Phase uniformity and spatially-static field distributions, essential characteristics of NZI materials, are also observed. Measurement of the same structure outside the NZI frequency range reveals existence of vortices in the power flow, as expected for conventional optical systems. Therefore, our results provide an important step forward in the development of ideal electromagnetic fluids, and introduce a tool to explore the subwavelength behavior of NZI media including fully vectorial and phase information. © 2022, The Author(s).Y.L. acknowledges partial support from National Natural Science Foundation of China (NSFC) under grant 62022045. I.L. acknowledges support from Ramón y Cajal fellowship RYC2018-024123-I and project RTI2018-093714-301J-I00 sponsored by MCIU/AEI/FEDER/UE and ERC Starting Grant 948504
On the Performance of RIS-Aided Spatial Scattering Modulation for mmWave Transmission
In this paper, we investigate a state-of-the-art reconfigurable intelligent
surface (RIS)-assisted spatial scattering modulation (SSM) scheme for
millimeter-wave (mmWave) systems, where a more practical scenario that the RIS
is near the transmitter while the receiver is far from RIS is considered. To
this end, the line-of-sight (LoS) and non-LoS links are utilized in the
transmitter-RIS and RIS-receiver channels, respectively. By employing the
maximum likelihood detector at the receiver, the conditional pairwise error
probability (CPEP) expression for the RIS-SSM scheme is derived under the two
scenarios that the received beam demodulation is correct or not. Furthermore,
the union upper bound of average bit error probability (ABEP) is obtained based
on the CPEP expression. Finally, the derivation results are exhaustively
validated by the Monte Carlo simulations.Comment: arXiv admin note: substantial text overlap with arXiv:2307.1466
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