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 *

788 related articles for article (PubMed ID: 30232517)

  • 1. Radiomics features to distinguish glioblastoma from primary central nervous system lymphoma on multi-parametric MRI.
    Kim Y; Cho HH; Kim ST; Park H; Nam D; Kong DS
    Neuroradiology; 2018 Dec; 60(12):1297-1305. PubMed ID: 30232517
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach.
    Suh HB; Choi YS; Bae S; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Lee SK
    Eur Radiol; 2018 Sep; 28(9):3832-3839. PubMed ID: 29626238
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Primary central nervous system lymphoma and glioblastoma differentiation based on conventional magnetic resonance imaging by high-throughput SIFT features.
    Chen Y; Li Z; Wu G; Yu J; Wang Y; Lv X; Ju X; Chen Z
    Int J Neurosci; 2018 Jul; 128(7):608-618. PubMed ID: 29183170
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Diffusion radiomics as a diagnostic model for atypical manifestation of primary central nervous system lymphoma: development and multicenter external validation.
    Kang D; Park JE; Kim YH; Kim JH; Oh JY; Kim J; Kim Y; Kim ST; Kim HS
    Neuro Oncol; 2018 Aug; 20(9):1251-1261. PubMed ID: 29438500
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multiparametric imaging-based differentiation of lymphoma and glioblastoma: using T1-perfusion, diffusion, and susceptibility-weighted MRI.
    Saini J; Kumar Gupta P; Awasthi A; Pandey CM; Singh A; Patir R; Ahlawat S; Sadashiva N; Mahadevan A; Kumar Gupta R
    Clin Radiol; 2018 Nov; 73(11):986.e7-986.e15. PubMed ID: 30197047
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine learning based on multi-parametric magnetic resonance imaging to differentiate glioblastoma multiforme from primary cerebral nervous system lymphoma.
    Nakagawa M; Nakaura T; Namimoto T; Kitajima M; Uetani H; Tateishi M; Oda S; Utsunomiya D; Makino K; Nakamura H; Mukasa A; Hirai T; Yamashita Y
    Eur J Radiol; 2018 Nov; 108():147-154. PubMed ID: 30396648
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Primary central nervous system lymphoma and atypical glioblastoma: multiparametric differentiation by using diffusion-, perfusion-, and susceptibility-weighted MR imaging.
    Kickingereder P; Wiestler B; Sahm F; Heiland S; Roethke M; Schlemmer HP; Wick W; Bendszus M; Radbruch A
    Radiology; 2014 Sep; 272(3):843-50. PubMed ID: 24814181
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Primary central nervous system lymphoma and atypical glioblastoma: differentiation using the initial area under the curve derived from dynamic contrast-enhanced MR and the apparent diffusion coefficient.
    Choi YS; Lee HJ; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Lee SK
    Eur Radiol; 2017 Apr; 27(4):1344-1351. PubMed ID: 27436023
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-Parametric Magnetic Resonance Imaging Based Convolutional Neural Network Model.
    Xia W; Hu B; Li H; Shi W; Tang Y; Yu Y; Geng C; Wu Q; Yang L; Yu Z; Geng D; Li Y
    J Magn Reson Imaging; 2021 Sep; 54(3):880-887. PubMed ID: 33694250
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine Learning-based Texture Analysis of Contrast-enhanced MR Imaging to Differentiate between Glioblastoma and Primary Central Nervous System Lymphoma.
    Kunimatsu A; Kunimatsu N; Yasaka K; Akai H; Kamiya K; Watadani T; Mori H; Abe O
    Magn Reson Med Sci; 2019 Jan; 18(1):44-52. PubMed ID: 29769456
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Differentiation between primary CNS lymphoma and glioblastoma: qualitative and quantitative analysis using arterial spin labeling MR imaging.
    You SH; Yun TJ; Choi HJ; Yoo RE; Kang KM; Choi SH; Kim JH; Sohn CH
    Eur Radiol; 2018 Sep; 28(9):3801-3810. PubMed ID: 29619520
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Role of intra-tumoral vasculature imaging features on susceptibility weighted imaging in differentiating primary central nervous system lymphoma from glioblastoma: a multiparametric comparison with pathological validation.
    Bhattacharjee R; Gupta M; Singh T; Sharma S; Khanna G; Parvaze SP; Patir R; Vaishya S; Ahlawat S; Singh A; Gupta RK
    Neuroradiology; 2022 Sep; 64(9):1801-1818. PubMed ID: 35435463
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Diagnostic utility of intravoxel incoherent motion mr imaging in differentiating primary central nervous system lymphoma from glioblastoma multiforme.
    Yamashita K; Hiwatashi A; Togao O; Kikuchi K; Kitamura Y; Mizoguchi M; Yoshimoto K; Kuga D; Suzuki SO; Baba S; Isoda T; Iwaki T; Iihara K; Honda H
    J Magn Reson Imaging; 2016 Nov; 44(5):1256-1261. PubMed ID: 27093558
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Differentiating Glioblastoma from Primary Central Nervous System Lymphoma: The Value of Shaping and Nonenhancing Peritumoral Hyperintense Gyral Lesion on FLAIR Imaging.
    Wang P; Shi YH; Li JY; Zhang CZ
    World Neurosurg; 2021 May; 149():e696-e704. PubMed ID: 33548537
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Quantitative Evaluation of Diffusion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Differentiation Between Primary Central Nervous System Lymphoma and Glioblastoma.
    Lu S; Wang S; Gao Q; Zhou M; Li Y; Cao P; Hong X; Shi H
    J Comput Assist Tomogr; 2017; 41(6):898-903. PubMed ID: 28806317
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Development and Validation of a MRI-Based Radiomics Prognostic Classifier in Patients with Primary Glioblastoma Multiforme.
    Chen X; Fang M; Dong D; Liu L; Xu X; Wei X; Jiang X; Qin L; Liu Z
    Acad Radiol; 2019 Oct; 26(10):1292-1300. PubMed ID: 30660472
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Incorporating diffusion- and perfusion-weighted MRI into a radiomics model improves diagnostic performance for pseudoprogression in glioblastoma patients.
    Kim JY; Park JE; Jo Y; Shim WH; Nam SJ; Kim JH; Yoo RE; Choi SH; Kim HS
    Neuro Oncol; 2019 Feb; 21(3):404-414. PubMed ID: 30107606
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation.
    Cheong EN; Park JE; Park SY; Jung SC; Kim HS
    Eur Radiol; 2024 Mar; 34(3):2008-2023. PubMed ID: 37665391
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Application of MR morphologic, diffusion tensor, and perfusion imaging in the classification of brain tumors using machine learning scheme.
    Shrot S; Salhov M; Dvorski N; Konen E; Averbuch A; Hoffmann C
    Neuroradiology; 2019 Jul; 61(7):757-765. PubMed ID: 30949746
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Multiparametric-MRI-Based Radiomics Model for Differentiating Primary Central Nervous System Lymphoma From Glioblastoma: Development and Cross-Vendor Validation.
    Xia W; Hu B; Li H; Geng C; Wu Q; Yang L; Yin B; Gao X; Li Y; Geng D
    J Magn Reson Imaging; 2021 Jan; 53(1):242-250. PubMed ID: 32864825
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 40.