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 *

295 related articles for article (PubMed ID: 36800947)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. 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]  

  • 7. 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]  

  • 8. 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]  

  • 9. 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]  

  • 10. 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]  

  • 11. [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]  

  • 12. The effect of deep learning reconstruction on abdominal CT densitometry and image quality: a systematic review and meta-analysis.
    van Stiphout JA; Driessen J; Koetzier LR; Ruules LB; Willemink MJ; Heemskerk JWT; van der Molen AJ
    Eur Radiol; 2022 May; 32(5):2921-2929. PubMed ID: 34913104
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. 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]  

  • 15. Abdominopelvic CT Image Quality: Evaluation of Thin (0.5-mm) Slices Using Deep Learning Reconstruction.
    Oostveen LJ; Smit EJ; Dekker HM; Buckens CF; Pegge SAH; de Lange F; Sechopoulos I; Prokop M
    AJR Am J Roentgenol; 2023 Mar; 220(3):381-388. PubMed ID: 36259592
    [No Abstract]   [Full Text] [Related]  

  • 16. A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities.
    Du H; Sui X; Zhao R; Wang J; Ming Y; Piao S; Wang J; Ma Z; Wang Y; Song L; Song W
    BMC Med Imaging; 2024 Jul; 24(1):163. PubMed ID: 38956583
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep learning reconstruction for high-resolution computed tomography images of the temporal bone: comparison with hybrid iterative reconstruction.
    Fujita N; Yasaka K; Hatano S; Sakamoto N; Kurokawa R; Abe O
    Neuroradiology; 2024 Jul; 66(7):1105-1112. PubMed ID: 38514472
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis.
    Zhang G; Zhang X; Xu L; Bai X; Jin R; Xu M; Yan J; Jin Z; Sun H
    Eur Radiol; 2022 Sep; 32(9):5954-5963. PubMed ID: 35357541
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Noise power spectrum properties of deep learning-based reconstruction and iterative reconstruction algorithms: Phantom and clinical study.
    Funama Y; Nakaura T; Hasegawa A; Sakabe D; Oda S; Kidoh M; Nagayama Y; Hirai T
    Eur J Radiol; 2023 Aug; 165():110914. PubMed ID: 37295358
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.
    Shirasaka T; Kojima T; Funama Y; Sakai Y; Kondo M; Mikayama R; Hamasaki H; Kato T; Ushijima Y; Asayama Y; Nishie A
    J Appl Clin Med Phys; 2021 Jul; 22(7):286-296. PubMed ID: 34159736
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.