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 *

139 related articles for article (PubMed ID: 37574664)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. 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]  

  • 7. CT angiography for planning transcatheter aortic valve replacement using automated tube voltage selection: Image quality and radiation exposure.
    Mangold S; De Cecco CN; Schoepf UJ; Kuhlman TS; Varga-Szemes A; Caruso D; Duguay TM; Tesche C; Vogl TJ; Nikolaou K; Steinberg DH; Wichmann JL
    Eur J Radiol; 2017 Jan; 86():276-283. PubMed ID: 28027760
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. [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]  

  • 10. Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.
    Otgonbaatar C; Ryu JK; Shin J; Woo JY; Seo JW; Shim H; Hwang DH
    Korean J Radiol; 2022 Nov; 23(11):1044-1054. PubMed ID: 36196766
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The impact of deep learning reconstruction on image quality and coronary CT angiography-derived fractional flow reserve values.
    Xu C; Xu M; Yan J; Li YY; Yi Y; Guo YB; Wang M; Li YM; Jin ZY; Wang YN
    Eur Radiol; 2022 Nov; 32(11):7918-7926. PubMed ID: 35596780
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Dark-Blood Computed Tomography Angiography Combined With Deep Learning Reconstruction for Cervical Artery Wall Imaging in Takayasu Arteritis.
    Su T; Zhang Z; Chen Y; Wang Y; Li Y; Xu M; Wang J; Li J; Tian X; Jin Z
    Korean J Radiol; 2024 Apr; 25(4):384-394. PubMed ID: 38528696
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep learning-based image restoration algorithm for coronary CT angiography.
    Tatsugami F; Higaki T; Nakamura Y; Yu Z; Zhou J; Lu Y; Fujioka C; Kitagawa T; Kihara Y; Iida M; Awai K
    Eur Radiol; 2019 Oct; 29(10):5322-5329. PubMed ID: 30963270
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Deep learning reconstruction allows for usage of contrast agent of lower concentration for coronary CTA than filtered back projection and hybrid iterative reconstruction.
    Otgonbaatar C; Ryu JK; Shin J; Kim HM; Seo JW; Shim H; Hwang DH
    Acta Radiol; 2023 Mar; 64(3):1007-1017. PubMed ID: 35979586
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Image quality and radiologists' subjective acceptance using model-based iterative and deep learning reconstructions as adjuncts to ultrahigh-resolution CT in low-dose contrast-enhanced abdominopelvic CT: phantom and clinical pilot studies.
    Nishikawa M; Machida H; Shimizu Y; Kariyasu T; Morisaka H; Adachi T; Nakai T; Sakaguchi K; Saito S; Matsumoto S; Koyanagi M; Yokoyama K
    Abdom Radiol (NY); 2022 Feb; 47(2):891-902. PubMed ID: 34914007
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Dynamic Computed Tomography Angiography for capturing vessel wall motion: A phantom study for optimal image reconstruction.
    Stam LB; Linden SML; Oostveen LJ; Hansen HHG; Aquarius R; Slump CH; de Korte CL; Bartels RHMA; Prokop M; Boogaarts HD; Meijer FJA
    PLoS One; 2023; 18(12):e0293353. PubMed ID: 38134125
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 7.