BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

419 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. 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. [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]  

  • 8. 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]  

  • 9. 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]  

  • 10. 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]  

  • 11. Improved stent sharpness evaluation with Super-Resolution deep learning reconstruction in coronary computed tomography angiography.
    Ryu JK; Kim KH; Otgonbaatar C; Kim DS; Shim H; Seo JW
    Br J Radiol; 2024 May; ():. PubMed ID: 38733576
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. 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]  

  • 14. 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]  

  • 15. 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]  

  • 16. 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]  

  • 17. 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]  

  • 18. 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]  

  • 19. 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]  

  • 20. 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]  

    [Next]    [New Search]
    of 21.