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 *

446 related articles for article (PubMed ID: 37432405)

  • 1. Improving image quality with super-resolution deep-learning-based reconstruction in coronary CT angiography.
    Nagayama Y; Emoto T; Kato Y; Kidoh M; Oda S; Sakabe D; Funama Y; Nakaura T; Hayashi H; Takada S; Uchimura R; Hatemura M; Tsujita K; Hirai T
    Eur Radiol; 2023 Dec; 33(12):8488-8500. PubMed ID: 37432405
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Coronary Stent Evaluation by CTA: Image Quality Comparison Between Super-Resolution Deep Learning Reconstruction and Other Reconstruction Algorithms.
    Nagayama Y; Emoto T; Hayashi H; Kidoh M; Oda S; Nakaura T; Sakabe D; Funama Y; Tabata N; Ishii M; Yamanaga K; Fujisue K; Takashio S; Yamamoto E; Tsujita K; Hirai T
    AJR Am J Roentgenol; 2023 Nov; 221(5):599-610. PubMed ID: 37377362
    [No Abstract]   [Full Text] [Related]  

  • 3. Deep learning-based reconstruction can improve the image quality of low radiation dose head CT.
    Nagayama Y; Iwashita K; Maruyama N; Uetani H; Goto M; Sakabe D; Emoto T; Nakato K; Shigematsu S; Kato Y; Takada S; Kidoh M; Oda S; Nakaura T; Hatemura M; Ueda M; Mukasa A; Hirai T
    Eur Radiol; 2023 May; 33(5):3253-3265. PubMed ID: 36973431
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Super-resolution deep learning reconstruction at coronary computed tomography angiography to evaluate the coronary arteries and in-stent lumen: an initial experience.
    Orii M; Sone M; Osaki T; Ueyama Y; Chiba T; Sasaki T; Yoshioka K
    BMC Med Imaging; 2023 Oct; 23(1):171. PubMed ID: 37904089
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Radiation Dose Reduction for 80-kVp Pediatric CT Using Deep Learning-Based Reconstruction: A Clinical and Phantom Study.
    Nagayama Y; Goto M; Sakabe D; Emoto T; Shigematsu S; Oda S; Tanoue S; Kidoh M; Nakaura T; Funama Y; Uchimura R; Takada S; Hayashi H; Hatemura M; Hirai T
    AJR Am J Roentgenol; 2022 Aug; 219(2):315-324. PubMed ID: 35195431
    [No Abstract]   [Full Text] [Related]  

  • 6. Improved stent sharpness evaluation with super-resolution deep learning reconstruction in coronary CT angiography.
    Ryu JK; Kim KH; Otgonbaatar C; Kim DS; Shim H; Seo JW
    Br J Radiol; 2024 Jun; 97(1159):1286-1294. PubMed ID: 38733576
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Lung-Optimized Deep-Learning-Based Reconstruction for Ultralow-Dose CT.
    Goto M; Nagayama Y; Sakabe D; Emoto T; Kidoh M; Oda S; Nakaura T; Taguchi N; Funama Y; Takada S; Uchimura R; Hayashi H; Hatemura M; Kawanaka K; Hirai T
    Acad Radiol; 2023 Mar; 30(3):431-440. PubMed ID: 35738988
    [TBL] [Abstract][Full Text] [Related]  

  • 8. [Deep learning reconstruction algorithm for coronary CT angiography in assessing obstructive coronary artery disease caused by calcified lesions: the clinical application value].
    Xu C; Yi Y; Li YY; Guo YB; Jin ZY; Wang YN
    Zhonghua Yi Xue Za Zhi; 2021 Oct; 101(39):3202-3207. PubMed ID: 34689531
    [No Abstract]   [Full Text] [Related]  

  • 9. Clinical acceptance of deep learning reconstruction for abdominal CT imaging: objective and subjective image quality and low-contrast detectability assessment.
    Bornet PA; Villani N; Gillet R; Germain E; Lombard C; Blum A; Gondim Teixeira PA
    Eur Radiol; 2022 May; 32(5):3161-3172. PubMed ID: 34989850
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Image quality comparison of lower extremity CTA between CT routine reconstruction algorithms and deep learning reconstruction.
    Zhang D; Mu C; Zhang X; Yan J; Xu M; Wang Y; Wang Y; Xue H; Chen Y; Jin Z
    BMC Med Imaging; 2023 Feb; 23(1):33. PubMed ID: 36800947
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Super-resolution deep-learning reconstruction for cardiac CT: impact of radiation dose and focal spot size on task-based image quality.
    Emoto T; Nagayama Y; Takada S; Sakabe D; Shigematsu S; Goto M; Nakato K; Yoshida R; Harai R; Kidoh M; Oda S; Nakaura T; Hirai T
    Phys Eng Sci Med; 2024 Jun; ():. PubMed ID: 38884668
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Ultra-High-Resolution Coronary CT Angiography With Photon-Counting Detector CT: Feasibility and Image Characterization.
    Mergen V; Sartoretti T; Baer-Beck M; Schmidt B; Petersilka M; Wildberger JE; Euler A; Eberhard M; Alkadhi H
    Invest Radiol; 2022 Dec; 57(12):780-788. PubMed ID: 35640019
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Radiation dose optimization potential of deep learning-based reconstruction for multiphase hepatic CT: A clinical and phantom study.
    Nagayama Y; Goto M; Sakabe D; Emoto T; Shigematsu S; Taguchi N; Maruyama N; Takada S; Uchimura R; Hayashi H; Kidoh M; Oda S; Nakaura T; Funama Y; Hatemura M; Hirai T
    Eur J Radiol; 2022 Jun; 151():110280. PubMed ID: 35381567
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Improving Image Quality and Reducing Radiation Dose for Pediatric CT by Using Deep Learning Reconstruction.
    Brady SL; Trout AT; Somasundaram E; Anton CG; Li Y; Dillman JR
    Radiology; 2021 Jan; 298(1):180-188. PubMed ID: 33201790
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep Learning Reconstruction at CT: Phantom Study of the Image Characteristics.
    Higaki T; Nakamura Y; Zhou J; Yu Z; Nemoto T; Tatsugami F; Awai K
    Acad Radiol; 2020 Jan; 27(1):82-87. PubMed ID: 31818389
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The Feasibility of Deep Learning-Based Reconstruction for Low-Tube-Voltage CT Angiography for Transcatheter Aortic Valve Implantation.
    Kojima T; Yamasaki Y; Matsuura Y; Mikayama R; Shirasaka T; Kondo M; Kamitani T; Kato T; Ishigami K; Yabuuchi H
    J Comput Assist Tomogr; 2024 Jan-Feb 01; 48(1):77-84. PubMed ID: 37574664
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Superior objective and subjective image quality of deep learning reconstruction for low-dose abdominal CT imaging in comparison with model-based iterative reconstruction and filtered back projection.
    Tamura A; Mukaida E; Ota Y; Kamata M; Abe S; Yoshioka K
    Br J Radiol; 2021 Jul; 94(1123):20201357. PubMed ID: 34142867
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Improvement of Spatial Resolution on Coronary CT Angiography by Using Super-Resolution Deep Learning Reconstruction.
    Tatsugami F; Higaki T; Kawashita I; Fukumoto W; Nakamura Y; Matsuura M; Lee TC; Zhou J; Cai L; Kitagawa T; Nakano Y; Awai K
    Acad Radiol; 2023 Nov; 30(11):2497-2504. PubMed ID: 36681533
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Deep learning-based reconstruction may improve non-contrast cerebral CT imaging compared to other current reconstruction algorithms.
    Oostveen LJ; Meijer FJA; de Lange F; Smit EJ; Pegge SA; Steens SCA; van Amerongen MJ; Prokop M; Sechopoulos I
    Eur Radiol; 2021 Aug; 31(8):5498-5506. PubMed ID: 33693996
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 23.