268 related articles for article (PubMed ID: 35731096)
1. Diagnostic Performance in Low- and High-Contrast Tasks of an Image-Based Denoising Algorithm Applied to Radiation Dose-Reduced Multiphase Abdominal CT Examinations.
Inoue A; Voss BA; Lee NJ; Takahashi H; Kozaka K; Heiken JP; Ehman EC; Vasconcelos R; Fidler JL; Lee YS; Mileto A; Johnson MP; Baer-Beck M; Weber NM; Michalak GJ; Halaweish A; Carter RE; McCollough CH; Fletcher JG
AJR Am J Roentgenol; 2023 Jan; 220(1):73-85. PubMed ID: 35731096
[No Abstract] [Full Text] [Related]
2. Prior iterative reconstruction (PIR) to lower radiation dose and preserve radiologist performance for multiphase liver CT: a multi-reader pilot study.
Mohammadinejad P; Ehman EC; Vasconcelos RN; Venkatesh SK; Hough DM; Lowe R; Lee YS; Nehra A; Dirks S; Holmes DR; Carter RE; Schmidt B; Halaweish AF; McCollough CH; Fletcher JG
Abdom Radiol (NY); 2020 Jan; 45(1):45-54. PubMed ID: 31705250
[TBL] [Abstract][Full Text] [Related]
3. Low-dose CT for the detection and classification of metastatic liver lesions: Results of the 2016 Low Dose CT Grand Challenge.
McCollough CH; Bartley AC; Carter RE; Chen B; Drees TA; Edwards P; Holmes DR; Huang AE; Khan F; Leng S; McMillan KL; Michalak GJ; Nunez KM; Yu L; Fletcher JG
Med Phys; 2017 Oct; 44(10):e339-e352. PubMed ID: 29027235
[TBL] [Abstract][Full Text] [Related]
4. Diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction algorithm for the detection of hypervascular liver lesions: a phantom study.
Nakamoto A; Tanaka Y; Juri H; Nakai G; Yoshikawa S; Narumi Y
Eur Radiol; 2017 Jul; 27(7):2995-3003. PubMed ID: 27957640
[TBL] [Abstract][Full Text] [Related]
5. Estimation of Observer Performance for Reduced Radiation Dose Levels in CT: Eliminating Reduced Dose Levels That Are Too Low Is the First Step.
Fletcher JG; Yu L; Fidler JL; Levin DL; DeLone DR; Hough DM; Takahashi N; Venkatesh SK; Sykes AG; White D; Lindell RM; Kotsenas AL; Campeau NG; Lehman VT; Bartley AC; Leng S; Holmes DR; Toledano AY; Carter RE; McCollough CH
Acad Radiol; 2017 Jul; 24(7):876-890. PubMed ID: 28262519
[TBL] [Abstract][Full Text] [Related]
6. Observer Performance with Varying Radiation Dose and Reconstruction Methods for Detection of Hepatic Metastases.
Fletcher JG; Fidler JL; Venkatesh SK; Hough DM; Takahashi N; Yu L; Johnson M; Leng S; Holmes DR; Carter R; McCollough CH
Radiology; 2018 Nov; 289(2):455-464. PubMed ID: 30204077
[TBL] [Abstract][Full Text] [Related]
7. Noise reduction to decrease radiation dose and improve conspicuity of hepatic lesions at contrast-enhanced 80-kV hepatic CT using projection space denoising.
Ehman EC; Guimarães LS; Fidler JL; Takahashi N; Ramirez-Giraldo JC; Yu L; Manduca A; Huprich JE; McCollough CH; Holmes D; Harmsen WS; Fletcher JG
AJR Am J Roentgenol; 2012 Feb; 198(2):405-11. PubMed ID: 22268185
[TBL] [Abstract][Full Text] [Related]
8. Image quality in liver CT: low-dose deep learning vs standard-dose model-based iterative reconstructions.
Park S; Yoon JH; Joo I; Yu MH; Kim JH; Park J; Kim SW; Han S; Ahn C; Kim JH; Lee JM
Eur Radiol; 2022 May; 32(5):2865-2874. PubMed ID: 34821967
[TBL] [Abstract][Full Text] [Related]
9. Observer performance for adaptive, image-based denoising and filtered back projection compared to scanner-based iterative reconstruction for lower dose CT enterography.
Fletcher JG; Hara AK; Fidler JL; Silva AC; Barlow JM; Carter RE; Bartley A; Shiung M; Holmes DR; Weber NK; Bruining DH; Yu L; McCollough CH
Abdom Imaging; 2015 Jun; 40(5):1050-9. PubMed ID: 25725794
[TBL] [Abstract][Full Text] [Related]
10. Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction.
Fletcher JG; Yu L; Li Z; Manduca A; Blezek DJ; Hough DM; Venkatesh SK; Brickner GC; Cernigliaro JC; Hara AK; Fidler JL; Lake DS; Shiung M; Lewis D; Leng S; Augustine KE; Carter RE; Holmes DR; McCollough CH
Radiology; 2015 Aug; 276(2):465-78. PubMed ID: 26020436
[TBL] [Abstract][Full Text] [Related]
11. Intraindividual comparison of diagnostic performance in patients with hepatic metastasis of full-dose standard and half-dose iterative reconstructions with dual-source abdominal computed tomography.
Park M; Chung YE; Lee HS; Choi JY; Park MS; Kim MJ; Kim KW
Invest Radiol; 2014 Apr; 49(4):195-200. PubMed ID: 24300843
[TBL] [Abstract][Full Text] [Related]
12. Impact of adaptive iterative dose reduction (AIDR) 3D on low-dose abdominal CT: comparison with routine-dose CT using filtered back projection.
Matsuki M; Murakami T; Juri H; Yoshikawa S; Narumi Y
Acta Radiol; 2013 Oct; 54(8):869-75. PubMed ID: 23761554
[TBL] [Abstract][Full Text] [Related]
13. Image Quality and Diagnostic Performance of Low-Dose Liver CT with Deep Learning Reconstruction versus Standard-Dose CT.
Lee DH; Lee JM; Lee CH; Afat S; Othman A
Radiol Artif Intell; 2024 Mar; 6(2):e230192. PubMed ID: 38231025
[TBL] [Abstract][Full Text] [Related]
14. Effect of Radiation Dose Reduction and Reconstruction Algorithm on Image Noise, Contrast, Resolution, and Detectability of Subtle Hypoattenuating Liver Lesions at Multidetector CT: Filtered Back Projection versus a Commercial Model-based Iterative Reconstruction Algorithm.
Solomon J; Marin D; Roy Choudhury K; Patel B; Samei E
Radiology; 2017 Sep; 284(3):777-787. PubMed ID: 28170300
[TBL] [Abstract][Full Text] [Related]
15. Evaluation of the impact of a novel denoising algorithm on image quality in dual-energy abdominal CT of obese patients.
Schwartz FR; Clark DP; Rigiroli F; Kalisz K; Wildman-Tobriner B; Thomas S; Wilson J; Badea CT; Marin D
Eur Radiol; 2023 Oct; 33(10):7056-7065. PubMed ID: 37083742
[TBL] [Abstract][Full Text] [Related]
16. Projection space denoising with bilateral filtering and CT noise modeling for dose reduction in CT.
Manduca A; Yu L; Trzasko JD; Khaylova N; Kofler JM; McCollough CM; Fletcher JG
Med Phys; 2009 Nov; 36(11):4911-9. PubMed ID: 19994500
[TBL] [Abstract][Full Text] [Related]
17. Observer Performance for Detection of Pulmonary Nodules at Chest CT over a Large Range of Radiation Dose Levels.
Fletcher JG; Levin DL; Sykes AG; Lindell RM; White DB; Kuzo RS; Suresh V; Yu L; Leng S; Holmes DR; Inoue A; Johnson MP; Carter RE; McCollough CH
Radiology; 2020 Dec; 297(3):699-707. PubMed ID: 32990514
[TBL] [Abstract][Full Text] [Related]
18. Low-Dose Abdominal CT Using a Deep Learning-Based Denoising Algorithm: A Comparison with CT Reconstructed with Filtered Back Projection or Iterative Reconstruction Algorithm.
Shin YJ; Chang W; Ye JC; Kang E; Oh DY; Lee YJ; Park JH; Kim YH
Korean J Radiol; 2020 Mar; 21(3):356-364. PubMed ID: 32090528
[TBL] [Abstract][Full Text] [Related]
19. Denoising of polychromatic CT images based on their own noise properties.
Kim JH; Chang Y; Ra JB
Med Phys; 2016 May; 43(5):2251. PubMed ID: 27147337
[TBL] [Abstract][Full Text] [Related]
20. Application of Deep Learning-Based Denoising Technique for Radiation Dose Reduction in Dynamic Abdominal CT: Comparison with Standard-Dose CT Using Hybrid Iterative Reconstruction Method.
Nagata M; Ichikawa Y; Domae K; Yoshikawa K; Kanii Y; Yamazaki A; Nagasawa N; Ishida M; Sakuma H
J Digit Imaging; 2023 Aug; 36(4):1578-1587. PubMed ID: 36944812
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
