Results 11 to 20 of about 1,957,229 (358)

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

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

State of the art: iterative CT reconstruction techniques [PDF]

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
Bastarrika, Gorka, DE CECCO, CARLO NICOLA, Geyer, Lucas L., LAGHI, ANDREA, Leipsic, Jonathon A., Meinel, Felix G., Nance, John W., Paul, Narinder S., RENGO, MARCO, Schoepf, U. Joseph   +9 more
core   +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

Iterative poisson surface reconstruction (iPSR) for unoriented points [PDF]

ACM Transactions on Graphics, 2022
Poisson surface reconstruction (PSR) remains a popular technique for reconstructing watertight surfaces from 3D point samples thanks to its efficiency, simplicity, and robustness.
Fei Hou, Chiyu Wang, Wencheng Wang, Hong Qin, Chen Qian, Ying He   +5 more
semanticscholar   +1 more source

Quantum Iterative Reconstruction for Abdominal Photon-counting Detector CT Improves Image Quality.

Radiology, 2022
Background An iterative reconstruction (IR) algorithm was introduced for clinical photon-counting detector (PCD) CT. Purpose To investigate the image quality and the optimal strength level of a quantum IR algorithm (QIR; Siemens Healthcare) for virtual ...
T. Sartoretti, Anna Landsmann, Dominik Nakhostin, M. Eberhard, Christian Röeren, Viktor Mergen, K. Higashigaito, R. Raupach, H. Alkadhi, A. Euler   +9 more
semanticscholar   +1 more source

Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung

Diagnostics, 2022
The aim of this study was to characterize image quality and to determine the optimal strength levels of a novel iterative reconstruction algorithm (quantum iterative reconstruction, QIR) for low-dose, ultra-high-resolution (UHR) photon-counting detector ...
T. Sartoretti, D. Racine, V. Mergen, Lisa Jungblut, P. Monnin, T. Flohr, K. Martini, T. Frauenfelder, H. Alkadhi, A. Euler   +9 more
semanticscholar   +1 more source

Deep learning reconstruction versus iterative reconstruction for cardiac CT angiography in a stroke imaging protocol: reduced radiation dose and improved image quality.

Quantitative Imaging in Medicine and Surgery, 2021
Background To assess the radiation dose and image quality of cardiac computed tomography angiography (CCTA) in an acute stroke imaging protocol using a deep learning reconstruction (DLR) method compared to a hybrid iterative reconstruction algorithm ...
A. Bernard, P. Comby, Brivaël Lemogne, K. Haioun, F. Ricolfi, O. Chevallier, R. Loffroy   +6 more
semanticscholar   +1 more source