BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

122 related articles for article (PubMed ID: 38237522)

  • 41. 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]  

  • 42. Standard and reduced radiation dose liver CT images: adaptive statistical iterative reconstruction versus model-based iterative reconstruction-comparison of findings and image quality.
    Shuman WP; Chan KT; Busey JM; Mitsumori LM; Choi E; Koprowicz KM; Kanal KM
    Radiology; 2014 Dec; 273(3):793-800. PubMed ID: 25170546
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Impact of an artificial intelligence deep-learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study.
    Greffier J; Si-Mohamed S; Frandon J; Loisy M; de Oliveira F; Beregi JP; Dabli D
    Med Phys; 2022 Aug; 49(8):5052-5063. PubMed ID: 35696272
    [TBL] [Abstract][Full Text] [Related]  

  • 44. A hybrid iterative reconstruction algorithm that improves the image quality of low-tube-voltage coronary CT angiography.
    Oda S; Utsunomiya D; Funama Y; Yonenaga K; Namimoto T; Nakaura T; Yamashita Y
    AJR Am J Roentgenol; 2012 May; 198(5):1126-31. PubMed ID: 22528903
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Lowering radiation dose during dedicated colorectal cancer MDCT: comparison of low tube voltage and sinogram-affirmed iterative reconstruction at 80 kVp versus blended dual-energy images in a population of patients with low body mass index.
    Chen CY; Hsu JS; Jaw TS; Kuo YT; Wu DC; Lee CH; Shih MC; Tsai TH; Kuo CH; Chen YT; Yang LH; Liu GC
    Abdom Imaging; 2015 Oct; 40(7):2867-76. PubMed ID: 25860034
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Image Quality and Lesion Detectability of Pancreatic Phase Thin-Slice Computed Tomography Images With a Deep Learning-Based Reconstruction Algorithm.
    Nakamoto A; Onishi H; Tsuboyama T; Fukui H; Ota T; Ogawa K; Yano K; Kiso K; Honda T; Tatsumi M; Tomiyama N
    J Comput Assist Tomogr; 2023 Sep-Oct 01; 47(5):698-703. PubMed ID: 37707398
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Impact of novel deep learning image reconstruction algorithm on diagnosis of contrast-enhanced liver computed tomography imaging: Comparing to adaptive statistical iterative reconstruction algorithm.
    Yang S; Bie Y; Pang G; Li X; Zhao K; Zhang C; Zhong H
    J Xray Sci Technol; 2021; 29(6):1009-1018. PubMed ID: 34569983
    [TBL] [Abstract][Full Text] [Related]  

  • 48. 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]  

  • 49. 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]  

  • 50. Impact of adaptive iterative dose reduction (AIDR) 3D on low-dose abdominal CT: comparison with routine-dose CT using filtered back projection.
    Matsuki M; Murakami T; Juri H; Yoshikawa S; Narumi Y
    Acta Radiol; 2013 Oct; 54(8):869-75. PubMed ID: 23761554
    [TBL] [Abstract][Full Text] [Related]  

  • 51. 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]  

  • 52. Full model-based iterative reconstruction (MBIR) in abdominal CT increases objective image quality, but decreases subjective acceptance.
    Laurent G; Villani N; Hossu G; Rauch A; Noël A; Blum A; Gondim Teixeira PA
    Eur Radiol; 2019 Aug; 29(8):4016-4025. PubMed ID: 30701327
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Combined Use of Automatic Tube Voltage Selection and Current Modulation with Iterative Reconstruction for CT Evaluation of Small Hypervascular Hepatocellular Carcinomas: Effect on Lesion Conspicuity and Image Quality.
    Lv P; Liu J; Zhang R; Jia Y; Gao J
    Korean J Radiol; 2015; 16(3):531-40. PubMed ID: 25995682
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Contrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study.
    Park CJ; Kim KW; Lee HJ; Kim MJ; Kim J
    Korean J Radiol; 2018; 19(5):957-964. PubMed ID: 30174486
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis.
    Lee T; Lee JM; Yoon JH; Joo I; Bae JS; Yoo J; Kim JH; Ahn C; Kim JH
    Eur Radiol; 2022 Sep; 32(9):6407-6417. PubMed ID: 35380228
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Effects of contrast enhancement boost postprocessing technique in combination with different reconstruction algorithms on the image quality of abdominal CT angiography.
    Xu J; Wang S; Wang X; Wang Y; Xue H; Yan J; Xu M; Jin Z
    Eur J Radiol; 2022 Sep; 154():110388. PubMed ID: 35714492
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Improving intracranial aneurysms image quality and diagnostic confidence with deep learning reconstruction in craniocervical CT angiography.
    Bai K; Wang T; Zhang G; Zhang M; Fu H; Feng Y; Liang K
    Acta Radiol; 2024 Jun; ():2841851241258220. PubMed ID: 38839094
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Application of low-dose CT combined with model-based iterative reconstruction algorithm in oncologic patients during follow-up: dose reduction and image quality.
    Ippolito D; Maino C; Pecorelli A; Salemi I; Gandola D; Riva L; Talei Franzesi C; Sironi S
    Br J Radiol; 2021 Aug; 94(1124):20201223. PubMed ID: 34233459
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance.
    Tanabe Y; Kido T; Kurata A; Fukuyama N; Yokoi T; Kido T; Uetani T; Vembar M; Dhanantwari A; Tokuyasu S; Yamashita N; Mochizuki T
    Int J Cardiovasc Imaging; 2017 Oct; 33(10):1609-1618. PubMed ID: 28409258
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Improving image quality with model-based iterative reconstruction algorithm for chest CT in children with reduced contrast concentration.
    Sun J; Hu D; Shen Y; Yang H; Chen C; Yin J; Peng Y
    Radiol Med; 2019 Jul; 124(7):595-601. PubMed ID: 30739289
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.