BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

185 related articles for article (PubMed ID: 37656175)

  • 1. Improving radiomics reproducibility using deep learning-based image conversion of CT reconstruction algorithms in hepatocellular carcinoma patients.
    Lee H; Chang W; Kim HY; Sung P; Cho J; Lee YJ; Kim YH
    Eur Radiol; 2024 Mar; 34(3):2036-2047. PubMed ID: 37656175
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep Learning-based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses.
    Choe J; Lee SM; Do KH; Lee G; Lee JG; Lee SM; Seo JB
    Radiology; 2019 Aug; 292(2):365-373. PubMed ID: 31210613
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep learning reconstruction improves radiomics feature stability and discriminative power in abdominal CT imaging: a phantom study.
    Michallek F; Genske U; Niehues SM; Hamm B; Jahnke P
    Eur Radiol; 2022 Jul; 32(7):4587-4595. PubMed ID: 35174400
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep learning image reconstruction algorithm reduces image noise while alters radiomics features in dual-energy CT in comparison with conventional iterative reconstruction algorithms: a phantom study.
    Zhong J; Xia Y; Chen Y; Li J; Lu W; Shi X; Feng J; Yan F; Yao W; Zhang H
    Eur Radiol; 2023 Feb; 33(2):812-824. PubMed ID: 36197579
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Comparison of Knowledge-based Iterative Model Reconstruction and Hybrid Reconstruction Techniques for Liver CT Evaluation of Hypervascular Hepatocellular Carcinoma.
    Park HJ; Lee JM; Park SB; Lee JB; Jeong YK; Yoon JH
    J Comput Assist Tomogr; 2016; 40(6):863-871. PubMed ID: 27331929
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Low-Dose Abdominal CT Using a Deep Learning-Based Denoising Algorithm: A Comparison with CT Reconstructed with Filtered Back Projection or Iterative Reconstruction Algorithm.
    Shin YJ; Chang W; Ye JC; Kang E; Oh DY; Lee YJ; Park JH; Kim YH
    Korean J Radiol; 2020 Mar; 21(3):356-364. PubMed ID: 32090528
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep learning versus iterative reconstruction on image quality and dose reduction in abdominal CT: a live animal study.
    Zhang JZ; Ganesh H; Raslau FD; Nair R; Escott E; Wang C; Wang G; Zhang J
    Phys Med Biol; 2022 Jul; 67(14):. PubMed ID: 35709707
    [No Abstract]   [Full Text] [Related]  

  • 8. Low tube voltage intermediate tube current liver MDCT: sinogram-affirmed iterative reconstruction algorithm for detection of hypervascular hepatocellular carcinoma.
    Yu MH; Lee JM; Yoon JH; Baek JH; Han JK; Choi BI; Flohr TG
    AJR Am J Roentgenol; 2013 Jul; 201(1):23-32. PubMed ID: 23789655
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep learning improves image quality and radiomics reproducibility for high-speed four-dimensional computed tomography reconstruction.
    Yang B; Chen X; Yuan S; Liu Y; Dai J; Men K
    Radiother Oncol; 2022 May; 170():184-189. PubMed ID: 35257852
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Iterative reconstruction: comparison of techniques for reduced-dose liver computed tomography following transarterial chemoembolization for hepatocellular carcinoma.
    Cha MJ; Jeong WK; Choi D; Kim YK; Lim S; Choi SY; Lee WJ
    Acta Radiol; 2016 Dec; 57(12):1429-1437. PubMed ID: 26792822
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep learning-based denoising algorithm in comparison to iterative reconstruction and filtered back projection: a 12-reader phantom study.
    Kim Y; Oh DY; Chang W; Kang E; Ye JC; Lee K; Kim HY; Kim YH; Park JH; Lee YJ; Lee KH
    Eur Radiol; 2021 Nov; 31(11):8755-8764. PubMed ID: 33885958
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Deep Learning-Based Computed Tomography Image Standardization to Improve Generalizability of Deep Learning-Based Hepatic Segmentation.
    Lee SB; Hong Y; Cho YJ; Jeong D; Lee J; Yoon SH; Lee S; Choi YH; Cheon JE
    Korean J Radiol; 2023 Apr; 24(4):294-304. PubMed ID: 36907592
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep Learning Algorithm for Reducing CT Slice Thickness: Effect on Reproducibility of Radiomic Features in Lung Cancer.
    Park S; Lee SM; Do KH; Lee JG; Bae W; Park H; Jung KH; Seo JB
    Korean J Radiol; 2019 Oct; 20(10):1431-1440. PubMed ID: 31544368
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep Learning-Based Image Conversion Improves the Reproducibility of Computed Tomography Radiomics Features: A Phantom Study.
    Lee SB; Cho YJ; Hong Y; Jeong D; Lee J; Kim SH; Lee S; Choi YH
    Invest Radiol; 2022 May; 57(5):308-317. PubMed ID: 34839305
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Low dose of contrast agent and low radiation liver computed tomography with deep-learning-based contrast boosting model in participants at high-risk for hepatocellular carcinoma: prospective, randomized, double-blind study.
    Kang HJ; Lee JM; Ahn C; Bae JS; Han S; Kim SW; Yoon JH; Han JK
    Eur Radiol; 2023 May; 33(5):3660-3670. PubMed ID: 36934202
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 80-kVp CT using Iterative Reconstruction in Image Space algorithm for the detection of hypervascular hepatocellular carcinoma: phantom and initial clinical experience.
    Hur S; Lee JM; Kim SJ; Park JH; Han JK; Choi BI
    Korean J Radiol; 2012; 13(2):152-64. PubMed ID: 22438682
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Using a single abdominal computed tomography image to differentiate five contrast-enhancement phases: A machine-learning algorithm for radiomics-based precision medicine.
    Dercle L; Ma J; Xie C; Chen AP; Wang D; Luk L; Revel-Mouroz P; Otal P; Peron JM; Rousseau H; Lu L; Schwartz LH; Mokrane FZ; Zhao B
    Eur J Radiol; 2020 Apr; 125():108850. PubMed ID: 32070870
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Assessment of a model-based, iterative reconstruction algorithm (MBIR) regarding image quality and dose reduction in liver computed tomography.
    Chang W; Lee JM; Lee K; Yoon JH; Yu MH; Han JK; Choi BI
    Invest Radiol; 2013 Aug; 48(8):598-606. PubMed ID: 23511193
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep learning imaging reconstruction of reduced-dose 40 keV virtual monoenergetic imaging for early detection of colorectal cancer liver metastases.
    Li S; Yuan L; Lu T; Yang X; Ren W; Wang L; Zhao J; Deng J; Liu X; Xue C; Sun Q; Zhang W; Zhou J
    Eur J Radiol; 2023 Nov; 168():111128. PubMed ID: 37816301
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Low-contrast-dose liver CT using low monoenergetic images with deep learning-based denoising for assessing hepatocellular carcinoma: a randomized controlled noninferiority trial.
    Bae JS; Lee JM; Kim SW; Park S; Han S; Yoon JH; Joo I; Hong H
    Eur Radiol; 2023 Jun; 33(6):4344-4354. PubMed ID: 36576547
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.