Results 1 to 10 of about 1,826,590 (358)

Iterative algorithm for reconstruction of entangled states [PDF]

Phys. Rev. A 63, R040303 (2001), 2000
An iterative algorithm for the reconstruction of an unknown quantum state from the results of incompatible measurements is proposed. It consists of Expectation-Maximization step followed by a unitary transformation of the eigenbasis of the density matrix. The procedure has been applied to the reconstruction of the entangled pair of photons.
J. Řeháček, Z. Hradil, Miroslav Ježek   +2 more
arxiv   +6 more sources

Multi-Scale Learned Iterative Reconstruction [PDF]

IEEE Transactions on Computational Imaging, 2020
Model-based learned iterative reconstruction methods have recently been shown to outperform classical reconstruction algorithms. Applicability of these methods to large scale inverse problems is however limited by the available memory for training and extensive training times, the latter due to computationally expensive forward models.
Andreas Hauptmann, Jonas Adler, Simon Arridge, Ozan Oktem   +3 more
openaire   +7 more sources

Iterative Reconstruction of Memory Kernels [PDF]

Journal of Chemical Theory and Computation, 2017
In recent years, it has become increasingly popular to construct coarse-grained models with non-Markovian dynamics to account for an incomplete separation of time scales. One challenge of a systematic coarse-graining procedure is the extraction of the dynamical properties, namely, the memory kernel, from equilibrium all-atom simulations.
Gerhard Jung, Martin Hanke, Friederike Schmid   +2 more
openaire   +6 more sources

Quality evaluation of image‐based iterative reconstruction for CT: Comparison with hybrid iterative reconstruction [PDF]

Journal of Applied Clinical Medical Physics, 2019
AbstractThe purpose of this study is to evaluate the physical image quality of a commercially available image‐based iterative reconstruction (IIR) system for two object contrasts to resemble a soft tissue (60 HU) and an enhanced vessel (270 HU), and compare the results with those of filtered back projection (FBP) and iterative reconstruction (IR).
Kosuke Matsubara, Tadanori Takata, Satoshi Kobayashi, Hiroji Nagata, Hiroki Kawashima, Katsuhiro Ichikawa   +5 more
openaire   +4 more sources

Deep iterative reconstruction for phase retrieval [PDF]

Applied Optics, 2019
Classical phase retrieval problem is the recovery of a constrained image from the magnitude of its Fourier transform. Although there are several well-known phase retrieval algorithms including the hybrid input-output (HIO) method, the reconstruction performance is generally sensitive to initialization and measurement noise.
Çağatay Işıl, Figen S. Oktem, Aykut Koç   +2 more
openaire   +7 more sources

Fast iterative reconstruction for photoacoustic tomography using learned physical model: Theoretical validation [PDF]

Photoacoustics, 2023
Iterative reconstruction has demonstrated superior performance in medical imaging under compressed, sparse, and limited-view sensing scenarios. However, iterative reconstruction algorithms are slow to converge and rely heavily on hand-crafted parameters ...
Ko-Tsung Hsu, Steven Guan, Parag V. Chitnis   +2 more
doaj   +2 more sources

Truncation effect reduction for fast iterative reconstruction in cone-beam CT [PDF]

BMC Medical Imaging, 2022
Background Iterative reconstruction for cone-beam computed tomography (CBCT) has been applied to improve image quality and reduce radiation dose. In a case where an object’s actual projection is larger than a flat panel detector, CBCT images contain ...
Sorapong Aootaphao, Saowapak S. Thongvigitmanee, Puttisak Puttawibul, Pairash Thajchayapong   +3 more
doaj   +2 more sources

Computed Tomography Image Quality Evaluation of a New Iterative Reconstruction Algorithm in the Abdomen (Adaptive Statistical Iterative Reconstruction–V) a Comparison With Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection Reconstructions [PDF]

Journal of Computer Assisted Tomography, 2018
Objective The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction–V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Methods and Materials
Eric P. Tamm, Ramon Q. Yap, Nicolaus A. Wagner-Bartak, Corey T. Jensen, Jia Sun, Martin Halmes Goodenberger, Xinming Liu, Shiva Gupta   +7 more
openaire   +4 more sources

Ultra Low Dose CT Pulmonary Angiography with Iterative Reconstruction. [PDF]

PLoS ONE, 2016
OBJECTIVE:Evaluation of a new iterative reconstruction algorithm (IMR) for detection/rule-out of pulmonary embolism (PE) in ultra-low dose computed tomography pulmonary angiography (CTPA).
Andreas Sauter, Thomas Koehler, Alexander A Fingerle, Bernhard Brendel, Vivien Richter, Michael Rasper, Ernst J Rummeny, Peter B Noël, Daniela Münzel   +8 more
doaj   +2 more sources

Optimizing computed tomography image reconstruction for focal hepatic lesions: Deep learning image reconstruction vs iterative reconstruction [PDF]

Heliyon
Background: Deep learning image reconstruction (DLIR) is a novel computed tomography (CT) reconstruction technique that minimizes image noise, enhances image quality, and enables radiation dose reduction.
Varin Jaruvongvanich, Kobkun Muangsomboon, Wanwarang Teerasamit, Voraparee Suvannarerg, Chulaluk Komoltri, Sastrawut Thammakittiphan, Wimonrat Lornimitdee, Witchuda Ritsamrej, Parinya Chaisue, Napapong Pongnapang, Piyaporn Apisarnthanarak   +10 more
doaj   +2 more sources