Masturzo L, Barca P, De Masi L, Marfisi D, Traino A, Cademartiri F
Eur Radiol Exp. 2025; 9(1):2.
PMID: 39747757
PMC: 11695565.
DOI: 10.1186/s41747-024-00541-2.
Hasegawa A, Kondo Y
Radiol Phys Technol. 2024; 17(4):947-954.
PMID: 39292344
DOI: 10.1007/s12194-024-00845-3.
Kim H, Lim S, Park M, Kim K, Kang S, Lee Y
Diagnostics (Basel). 2024; 14(15).
PMID: 39125465
PMC: 11312005.
DOI: 10.3390/diagnostics14151589.
Inoue T, Ichikawa K, Hara T, Ohashi K, Sato K, Kawashima H
Radiol Phys Technol. 2024; 17(1):238-247.
PMID: 38198065
DOI: 10.1007/s12194-023-00771-w.
Gibson N, Lee A, Bencsik M
Radiol Phys Technol. 2023; 17(1):112-123.
PMID: 37955819
DOI: 10.1007/s12194-023-00755-w.
Method for measuring noise-power spectrum independent of the effect of extracting the region of interest from a noise image.
Narita A, Ohsugi Y, Ohkubo M, Fukaya T, Sakai K, Noto Y
Radiol Phys Technol. 2023; 16(4):471-477.
PMID: 37515623
DOI: 10.1007/s12194-023-00733-2.
Noise reduction performance of a deep learning-based reconstruction in brain computed tomography images acquired with organ-based tube current modulation.
Watanabe S, Kono Y, Kitaguchi S, Kosaka H, Ishii K
Phys Eng Sci Med. 2023; 46(3):1153-1162.
PMID: 37266875
DOI: 10.1007/s13246-023-01282-z.
Properties of the SSIM metric in medical image assessment: correspondence between measurements and the spatial frequency spectrum.
Maruyama S
Phys Eng Sci Med. 2023; 46(3):1131-1141.
PMID: 37213052
DOI: 10.1007/s13246-023-01280-1.
Comparison of image quality, arterial depiction, and radiation dose between two rapid kVp-switching dual-energy CT scanners in CT angiography at 40-keV.
Kaga T, Noda Y, Nagata S, Kawai N, Miyoshi T, Hyodo F
Jpn J Radiol. 2023; 41(11):1298-1307.
PMID: 37212946
PMC: 10613589.
DOI: 10.1007/s11604-023-01448-5.
Evaluation of Image Quality and Detectability of Deep Learning Image Reconstruction (DLIR) Algorithm in Single- and Dual-energy CT.
Zhong J, Shen H, Chen Y, Xia Y, Shi X, Lu W
J Digit Imaging. 2023; 36(4):1390-1407.
PMID: 37071291
PMC: 10406981.
DOI: 10.1007/s10278-023-00806-z.
Usefulness of copper filters in digital chest radiography based on the relationship between effective detective quantum efficiency and deep learning-based segmentation accuracy of the tumor area.
Onodera S, Kondo Y, Ishizawa S, Kawabata T, Ishii H
Radiol Phys Technol. 2023; 16(2):299-309.
PMID: 37046154
DOI: 10.1007/s12194-023-00719-0.
Impact of ROI Size on the Accuracy of Noise Measurement in CT on Computational and ACR Phantoms.
Anam C, Triadyaksa P, Naufal A, Arifin Z, Muhlisin Z, Setiawati E
J Biomed Phys Eng. 2022; 12(4):359-368.
PMID: 36059282
PMC: 9395624.
DOI: 10.31661/jbpe.v0i0.2202-1457.
Fully automated image quality evaluation on patient CT: Multi-vendor and multi-reconstruction study.
Chun M, Choi J, Kim S, Ahn C, Kim J
PLoS One. 2022; 17(7):e0271724.
PMID: 35857804
PMC: 9299323.
DOI: 10.1371/journal.pone.0271724.
Accuracy of two deep learning-based reconstruction methods compared with an adaptive statistical iterative reconstruction method for solid and ground-glass nodule volumetry on low-dose and ultra-low-dose chest computed tomography: A phantom study.
Kim C, Kwack T, Kim W, Cha J, Yang Z, Yong H
PLoS One. 2022; 17(6):e0270122.
PMID: 35737734
PMC: 9223620.
DOI: 10.1371/journal.pone.0270122.
Evaluation of Abdominal CT Obtained Using a Deep Learning-Based Image Reconstruction Engine Compared with CT Using Adaptive Statistical Iterative Reconstruction.
Yoo Y, Choi I, Yeom S, Cha S, Jung Y, Han H
J Belg Soc Radiol. 2022; 106(1):15.
PMID: 35480337
PMC: 8992765.
DOI: 10.5334/jbsr.2638.
Unenhanced abdominal low-dose CT reconstructed with deep learning-based image reconstruction: image quality and anatomical structure depiction.
Kaga T, Noda Y, Mori T, Kawai N, Miyoshi T, Hyodo F
Jpn J Radiol. 2022; 40(7):703-711.
PMID: 35286578
PMC: 9252942.
DOI: 10.1007/s11604-022-01259-0.
Image quality assessment of pediatric chest and abdomen CT by deep learning reconstruction.
Yoon H, Kim J, Lim H, Lee M
BMC Med Imaging. 2021; 21(1):146.
PMID: 34629049
PMC: 8503996.
DOI: 10.1186/s12880-021-00677-2.
Improvement of Image Quality Using Hybrid Iterative Reconstruction with Noise Power Spectrum Model in Computed Tomography During Hepatic Arteriography.
Hamasaki H, Shirasaka T, Ushijima Y, Akamine H, Takayama Y, Kubo Y
J Belg Soc Radiol. 2021; 105(1):43.
PMID: 34611577
PMC: 8447979.
DOI: 10.5334/jbsr.2444.
An Improved Method of Automated Noise Measurement System in CT Images.
Anam C, Arif I, Haryanto F, Lestari F, Widita R, Budi W
J Biomed Phys Eng. 2021; 11(2):163-174.
PMID: 33937124
PMC: 8064134.
DOI: 10.31661/jbpe.v0i0.1198.
Image Noise Covariance Can be Adjusted by a Noise Weighted Filtered Backprojection Algorithm.
Zeng G
IEEE Trans Radiat Plasma Med Sci. 2020; 3(6):668-674.
PMID: 32258855
PMC: 7120744.
DOI: 10.1109/trpms.2019.2900244.