These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

655 related articles for article (PubMed ID: 32100091)

  • 1. Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study.
    Greffier J; Hamard A; Pereira F; Barrau C; Pasquier H; Beregi JP; Frandon J
    Eur Radiol; 2020 Jul; 30(7):3951-3959. PubMed ID: 32100091
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Performance evaluation of deep learning image reconstruction algorithm for dual-energy spectral CT imaging: A phantom study.
    Li H; Li Z; Gao S; Hu J; Yang Z; Peng Y; Sun J
    J Xray Sci Technol; 2024; 32(3):513-528. PubMed ID: 38393883
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Detectability of Small Low-Attenuation Lesions With Deep Learning CT Image Reconstruction: A 24-Reader Phantom Study.
    Toia GV; Zamora DA; Singleton M; Liu A; Tan E; Leng S; Shuman WP; Kanal KM; Mileto A
    AJR Am J Roentgenol; 2023 Feb; 220(2):283-295. PubMed ID: 36129222
    [No Abstract]   [Full Text] [Related]  

  • 4. Task-based characterization of a deep learning image reconstruction and comparison with filtered back-projection and a partial model-based iterative reconstruction in abdominal CT: A phantom study.
    Racine D; Becce F; Viry A; Monnin P; Thomsen B; Verdun FR; Rotzinger DC
    Phys Med; 2020 Aug; 76():28-37. PubMed ID: 32574999
    [TBL] [Abstract][Full Text] [Related]  

  • 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; Li J; Xing Y; Hu Y; Ge X; Ding D; Jiang Z; Yao W
    J Digit Imaging; 2023 Aug; 36(4):1390-1407. PubMed ID: 37071291
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep learning image reconstruction algorithm for abdominal multidetector CT at different tube voltages: assessment of image quality and radiation dose in a phantom study.
    Park HJ; Choi SY; Lee JE; Lim S; Lee MH; Yi BH; Cha JG; Min JH; Lee B; Jung Y
    Eur Radiol; 2022 Jun; 32(6):3974-3984. PubMed ID: 35064803
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Impact of noise reduction on radiation dose reduction potential of virtual monochromatic spectral images: Comparison of phantom images with conventional 120 kVp images using deep learning image reconstruction and hybrid iterative reconstruction.
    Masuda S; Yamada Y; Minamishima K; Owaki Y; Yamazaki A; Jinzaki M
    Eur J Radiol; 2022 Apr; 149():110198. PubMed ID: 35168172
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely?
    Lyu P; Liu N; Harrawood B; Solomon J; Wang H; Chen Y; Rigiroli F; Ding Y; Schwartz FR; Jiang H; Lowry C; Wang L; Samei E; Gao J; Marin D
    Eur Radiol; 2023 Mar; 33(3):1629-1640. PubMed ID: 36323984
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improved image quality and dose reduction in abdominal CT with deep-learning reconstruction algorithm: a phantom study.
    Greffier J; Durand Q; Frandon J; Si-Mohamed S; Loisy M; de Oliveira F; Beregi JP; Dabli D
    Eur Radiol; 2023 Jan; 33(1):699-710. PubMed ID: 35864348
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Phantom task-based image quality assessment of three generations of rapid kV-switching dual-energy CT systems on virtual monoenergetic images.
    Greffier J; Viry A; Barbotteau Y; Frandon J; Loisy M; de Oliveira F; Beregi JP; Dabli D
    Med Phys; 2022 Apr; 49(4):2233-2244. PubMed ID: 35184293
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Noise and spatial resolution properties of a commercially available deep learning-based CT reconstruction algorithm.
    Solomon J; Lyu P; Marin D; Samei E
    Med Phys; 2020 Sep; 47(9):3961-3971. PubMed ID: 32506661
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Impact of an artificial intelligence deep-learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study.
    Greffier J; Si-Mohamed S; Frandon J; Loisy M; de Oliveira F; Beregi JP; Dabli D
    Med Phys; 2022 Aug; 49(8):5052-5063. PubMed ID: 35696272
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep learning reconstruction for contrast-enhanced CT of the upper abdomen: similar image quality with lower radiation dose in direct comparison with iterative reconstruction.
    Nam JG; Hong JH; Kim DS; Oh J; Goo JM
    Eur Radiol; 2021 Aug; 31(8):5533-5543. PubMed ID: 33555354
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Comparison of two versions of a deep learning image reconstruction algorithm on CT image quality and dose reduction: A phantom study.
    Greffier J; Dabli D; Frandon J; Hamard A; Belaouni A; Akessoul P; Fuamba Y; Le Roy J; Guiu B; Beregi JP
    Med Phys; 2021 Oct; 48(10):5743-5755. PubMed ID: 34418110
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Spatial resolution, noise properties, and detectability index of a deep learning reconstruction algorithm for dual-energy CT of the abdomen.
    Thor D; Titternes R; Poludniowski G
    Med Phys; 2023 May; 50(5):2775-2786. PubMed ID: 36774193
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.
    Lyu P; Li Z; Chen Y; Wang H; Liu N; Liu J; Zhan P; Liu X; Shang B; Wang L; Gao J
    Eur Radiol; 2024 Jan; 34(1):28-38. PubMed ID: 37532899
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep-learning image reconstruction for image quality evaluation and accurate bone mineral density measurement on quantitative CT: A phantom-patient study.
    Li Y; Jiang Y; Yu X; Ren B; Wang C; Chen S; Ma D; Su D; Liu H; Ren X; Yang X; Gao J; Wu Y
    Front Endocrinol (Lausanne); 2022; 13():884306. PubMed ID: 36034436
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT.
    Son W; Kim M; Hwang JY; Kim YW; Park C; Choo KS; Kim TU; Jang JY
    Korean J Radiol; 2022 Jul; 23(7):752-762. PubMed ID: 35695313
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Low-dose whole-body CT using deep learning image reconstruction: image quality and lesion detection.
    Noda Y; Kaga T; Kawai N; Miyoshi T; Kawada H; Hyodo F; Kambadakone A; Matsuo M
    Br J Radiol; 2021 May; 94(1121):20201329. PubMed ID: 33571010
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Deep learning image reconstruction algorithm reduces image noise while alters radiomics features in dual-energy CT in comparison with conventional iterative reconstruction algorithms: a phantom study.
    Zhong J; Xia Y; Chen Y; Li J; Lu W; Shi X; Feng J; Yan F; Yao W; Zhang H
    Eur Radiol; 2023 Feb; 33(2):812-824. PubMed ID: 36197579
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 33.