Results 121 to 130 of about 1,826,590 (358)

Optimization of Analytical Reconstruction Algorithms for Arbitrary CBCT Trajectory Using Deep Learning

e-Journal of Nondestructive Testing
This study addresses the challenge of applying analytical methods for Cone Beam Computed Tomography (CBCT) reconstructions along arbitrary trajectories instead of iterative methods.
Yuzhong Zhou, Linda-Sophie Schneider, Yipeng Sun, Andreas K. Maier   +3 more
doaj   +1 more source

Degradation of CT Low-Contrast Spatial Resolution Due to the Use of Iterative Reconstruction and Reduced Dose Levels.

Radiology, 2015
PURPOSE To determine the dose reduction that could be achieved without degrading low-contrast spatial resolution (LCR) performance for two commercial iterative reconstruction (IR) techniques, each evaluated at two strengths with many repeated scans ...
C. McCollough, Lifeng Yu, J. Kofler, S. Leng, Yi Zhang, Zhoubo Li, R. Carter   +6 more
semanticscholar   +1 more source

Roulette‐Inspired Physical Unclonable Functions: Stochastic yet Deterministic Multi‐Bit Patterning through the Solutal Marangoni Effect

Advanced Functional Materials, EarlyView.
Geometric multi‐bit patterning based on dynamic wetting and dewetting phenomena creates roulette‐like Physical Unclonable Function (PUF) labels with stochastic yet deterministic properties. This method leverages the solutal‐Marangoni effect for high randomness while achieving deterministic multinary patterns through polygonal confinement of binary ...
Yeongin Cho, Jeongsu Pyeon, Hanhwi Jang, Gwangsik Mun, Jaimin Kang, Byong‐Guk Park, Geon Yeong Kim, Hyoungsoo Kim, Yeon Sik Jung   +8 more
wiley   +1 more source

Convolution kernel and iterative reconstruction affect the diagnostic performance of radiomics and deep learning in lung adenocarcinoma pathological subtypes

Thoracic Cancer, 2019
Background The aim of this study was to investigate the influence of convolution kernel and iterative reconstruction on the diagnostic performance of radiomics and deep learning (DL) in lung adenocarcinomas.
Wei Zhao, Wei Zhang, Yingli Sun, Yuxiang Ye, Jiancheng Yang, Wufei Chen, Pan Gao, Jianying Li, Cheng Li, Liang Jin, Peijun Wang, Yanqing Hua, Ming Li   +12 more
doaj   +1 more source

Backward reconstruction in acoustical holography based on iterative inversion techniques [PDF]

, 1988
Mingsian R. Bai, Anna L. Pate
openalex   +1 more source

Temperature‐Resilient Polymeric Memristors for Effective Deblurring in Static and Dynamic Imaging

Advanced Functional Materials, EarlyView.
A thermally stable organic memristor based on a thiadiazolobenzotriazole (TBZ) and 2,5‐Dioctyl‐3,6‐di(thiophen‐2‐yl)pyrrolo[3,4‐c]pyrrole‐1,4(2H,5H)‐dione (DPP)‐based conjugated polymer is presented, demonstrating reliable, gradual resistance switching across a wide temperature range (153–573 K).
Ziyu Lv, Ming‐Hao Jiang, Hui‐Ying Liu, Qing‐Xiu Li, Tao Xie, Jingya Yang, Yan Wang, Yongbiao Zhai, Guanglong Ding, Shirui Zhu, Jia‐Hua Li, Miao Zhang, Ye Zhou, Bobo Tian, Wai‐Yeung Wong, Su‐Ting Han   +15 more
wiley   +1 more source

State of the Art: Iterative CT Reconstruction Techniques.

Radiology, 2015
Owing to recent advances in computing power, iterative reconstruction (IR) algorithms have become a clinically viable option in computed tomographic (CT) imaging. Substantial evidence is accumulating about the advantages of IR algorithms over established
L. Geyer, U. Schoepf, F. Meinel, J. Nance, G. Bastarrika, J. Leipsic, N. Paul, M. Rengo, A. Laghi, C. D. Cecco, C. D. Cecco   +10 more
semanticscholar   +1 more source

Omnidirectional Transmissive Acoustic Metasurfaces Based on Goldberg Polyhedra

Advanced Functional Materials, EarlyView.
This study introduces omnidirectional acoustic metasurfaces capable of manipulating wavefronts in multiple arbitrary directions simultaneously. A full‐stack pipeline for design, optimization, and fabrication is presented to construct near‐spherical holograms based on Goldberg polyhedra.
Andrea Achilleos, James Hardwick, Ryuji Hirayama, Sriram Subramanian   +3 more
wiley   +1 more source

<title>Preconditioned iterative methods for superresolution image reconstruction with multisensors</title> [PDF]

, 2000
Michael K. Ng, Kenton Sze
openalex   +1 more source

Statistical Iterative CBCT Reconstruction Based on Neural Network

IEEE Transactions on Medical Imaging, 2018
Cone-beam computed tomography (CBCT) plays an important role in radiation therapy. Statistical iterative reconstruction (SIR) algorithms with specially designed penalty terms provide good performance for low-dose CBCT imaging.
Binbin Chen, Kaijia Xiang, Zaiwen Gong, Jing Wang, Shan Tan   +4 more
semanticscholar   +1 more source