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 *

168 related articles for article (PubMed ID: 37179907)

  • 1. Improving image quality and resolution of coronary arteries in coronary computed tomography angiography by using high-definition scans and deep learning image reconstruction.
    Wang Y; Wang G; Huang X; Zhao W; Zeng Q; Li Y; Guo J
    Quant Imaging Med Surg; 2023 May; 13(5):2933-2940. PubMed ID: 37179907
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Effect of deep learning image reconstruction with high-definition standard scan mode on image quality of coronary stents and arteries.
    Liu M; Chen X; Liu W; Guo Y; Zhu Y; Duan Y; Huang W; Kong W; Yan C; Qin J
    Quant Imaging Med Surg; 2024 Feb; 14(2):1616-1635. PubMed ID: 38415168
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Application of deep learning image reconstruction-high algorithm in one-stop coronary and carotid-cerebrovascular CT angiography with low radiation and contrast doses.
    Li W; Huang W; Li P; Wen Y; Shuai T; He Y; You Y; Yu J; Diao K; Song B
    Quant Imaging Med Surg; 2024 Feb; 14(2):1860-1872. PubMed ID: 38415146
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Validation of deep-learning image reconstruction for coronary computed tomography angiography: Impact on noise, image quality and diagnostic accuracy.
    Benz DC; Benetos G; Rampidis G; von Felten E; Bakula A; Sustar A; Kudura K; Messerli M; Fuchs TA; Gebhard C; Pazhenkottil AP; Kaufmann PA; Buechel RR
    J Cardiovasc Comput Tomogr; 2020; 14(5):444-451. PubMed ID: 31974008
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Application of deep learning image reconstruction algorithm to improve image quality in CT angiography of children with Takayasu arteritis.
    Sun J; Li H; Li H; Li M; Gao Y; Zhou Z; Peng Y
    J Xray Sci Technol; 2022; 30(1):177-184. PubMed ID: 34806646
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The value of a deep learning image reconstruction algorithm in whole-brain computed tomography perfusion in patients with acute ischemic stroke.
    Lei L; Zhou Y; Guo X; Wang L; Zhao X; Wang H; Ma J; Yue S
    Quant Imaging Med Surg; 2023 Dec; 13(12):8173-8189. PubMed ID: 38106310
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Improving spatial resolution and diagnostic confidence with thinner slice and deep learning image reconstruction in contrast-enhanced abdominal CT.
    Cao L; Liu X; Qu T; Cheng Y; Li J; Li Y; Chen L; Niu X; Tian Q; Guo J
    Eur Radiol; 2023 Mar; 33(3):1603-1611. PubMed ID: 36190531
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Impact of deep learning-based image reconstruction on image quality compared with adaptive statistical iterative reconstruction-Veo in renal and adrenal computed tomography.
    Bie Y; Yang S; Li X; Zhao K; Zhang C; Zhong H
    J Xray Sci Technol; 2022; 30(3):409-418. PubMed ID: 35124575
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. A deep-learning reconstruction algorithm that improves the image quality of low-tube-voltage coronary CT angiography.
    Wang M; Fan J; Shi X; Qin L; Yan F; Yang W
    Eur J Radiol; 2022 Jan; 146():110070. PubMed ID: 34856519
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Iterative reconstruction
    Qu T; Guo Y; Li J; Cao L; Li Y; Chen L; Sun J; Lu X; Guo J
    Br J Radiol; 2022 Dec; 95(1140):20220196. PubMed ID: 36341682
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A study of using a deep learning image reconstruction to improve the image quality of extremely low-dose contrast-enhanced abdominal CT for patients with hepatic lesions.
    Cao L; Liu X; Li J; Qu T; Chen L; Cheng Y; Hu J; Sun J; Guo J
    Br J Radiol; 2021 Feb; 94(1118):20201086. PubMed ID: 33242256
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep Learning Image Reconstruction Algorithm for CCTA: Image Quality Assessment and Clinical Application.
    Catapano F; Lisi C; Savini G; Olivieri M; Figliozzi S; Caracciolo A; Monti L; Francone M
    J Comput Assist Tomogr; 2024 Mar-Apr 01; 48(2):217-221. PubMed ID: 37621087
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Validation of Deep-Learning Image Reconstruction for Low-Dose Chest Computed Tomography Scan: Emphasis on Image Quality and Noise.
    Kim JH; Yoon HJ; Lee E; Kim I; Cha YK; Bak SH
    Korean J Radiol; 2021 Jan; 22(1):131-138. PubMed ID: 32729277
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The application value of a vendor-specific deep learning image reconstruction algorithm in "triple low" head and neck computed tomography angiography.
    Zhang Q; Lin Y; Zhang H; Ding J; Pan J; Zhang S
    Quant Imaging Med Surg; 2024 Apr; 14(4):2955-2967. PubMed ID: 38617163
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The value of using a deep learning image reconstruction algorithm of thinner slice thickness to balance the image noise and spatial resolution in low-dose abdominal CT.
    Wang H; Li X; Wang T; Li J; Sun T; Chen L; Cheng Y; Jia X; Niu X; Guo J
    Quant Imaging Med Surg; 2023 Mar; 13(3):1814-1824. PubMed ID: 36915333
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The image quality of deep-learning image reconstruction of chest CT images on a mediastinal window setting.
    Hata A; Yanagawa M; Yoshida Y; Miyata T; Kikuchi N; Honda O; Tomiyama N
    Clin Radiol; 2021 Feb; 76(2):155.e15-155.e23. PubMed ID: 33220941
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Multi-reader multiparametric DECT study evaluating different strengths of iterative and deep learning-based image reconstruction techniques.
    Cao J; Mroueh N; Lennartz S; Mercaldo ND; Pisuchpen N; Kongboonvijit S; Srinivas Rao S; Yuenyongsinchai K; Pierce TT; Sertic M; Chung R; Kambadakone AR
    Eur Radiol; 2024 Jul; ():. PubMed ID: 39046499
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Impact of deep learning-based image reconstruction on image quality and lesion visibility in renal computed tomography at different doses.
    Bie Y; Yang S; Li X; Zhao K; Zhang C; Zhong H
    Quant Imaging Med Surg; 2023 Apr; 13(4):2197-2207. PubMed ID: 37064389
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.