BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

193 related articles for article (PubMed ID: 32974873)

  • 1. Deep Learning Model for the Automated Detection and Histopathological Prediction of Meningioma.
    Zhang H; Mo J; Jiang H; Li Z; Hu W; Zhang C; Wang Y; Wang X; Liu C; Zhao B; Zhang J; Zhang K
    Neuroinformatics; 2021 Jul; 19(3):393-402. PubMed ID: 32974873
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI.
    Laukamp KR; Thiele F; Shakirin G; Zopfs D; Faymonville A; Timmer M; Maintz D; Perkuhn M; Borggrefe J
    Eur Radiol; 2019 Jan; 29(1):124-132. PubMed ID: 29943184
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automated Meningioma Segmentation in Multiparametric MRI : Comparable Effectiveness of a Deep Learning Model and Manual Segmentation.
    Laukamp KR; Pennig L; Thiele F; Reimer R; Görtz L; Shakirin G; Zopfs D; Timmer M; Perkuhn M; Borggrefe J
    Clin Neuroradiol; 2021 Jun; 31(2):357-366. PubMed ID: 32060575
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep learning-based automatic segmentation of meningioma from T1-weighted contrast-enhanced MRI for preoperative meningioma differentiation using radiomic features.
    Yang L; Wang T; Zhang J; Kang S; Xu S; Wang K
    BMC Med Imaging; 2024 Mar; 24(1):56. PubMed ID: 38443817
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Accuracy of deep learning to differentiate the histopathological grading of meningiomas on MR images: A preliminary study.
    Banzato T; Causin F; Della Puppa A; Cester G; Mazzai L; Zotti A
    J Magn Reson Imaging; 2019 Oct; 50(4):1152-1159. PubMed ID: 30896065
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.
    Chen H; Li S; Zhang Y; Liu L; Lv X; Yi Y; Ruan G; Ke C; Feng Y
    Eur Radiol; 2022 Oct; 32(10):7248-7259. PubMed ID: 35420299
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Intelligent noninvasive meningioma grading with a fully automatic segmentation using interpretable multiparametric deep learning.
    Jun Y; Park YW; Shin H; Shin Y; Lee JR; Han K; Ahn SS; Lim SM; Hwang D; Lee SK
    Eur Radiol; 2023 Sep; 33(9):6124-6133. PubMed ID: 37052658
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Radiomic signatures of meningiomas using the Ki-67 proliferation index as a prognostic marker of clinical outcomes.
    Khanna O; Fathi Kazerooni A; Arif S; Mahtabfar A; Momin AA; Andrews CE; Hafazalla K; Baldassari MP; Velagapudi L; Garcia JA; Sako C; Farrell CJ; Evans JJ; Judy KD; Andrews DW; Flanders AE; Shi W; Davatzikos C
    Neurosurg Focus; 2023 Jun; 54(6):E17. PubMed ID: 37552657
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis.
    Maniar KM; Lassarén P; Rana A; Yao Y; Tewarie IA; Gerstl JVE; Recio Blanco CM; Power LH; Mammi M; Mattie H; Smith TR; Mekary RA
    World Neurosurg; 2023 Nov; 179():e119-e134. PubMed ID: 37574189
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.
    Park YW; Oh J; You SC; Han K; Ahn SS; Choi YS; Chang JH; Kim SH; Lee SK
    Eur Radiol; 2019 Aug; 29(8):4068-4076. PubMed ID: 30443758
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Correlation of volumetric growth and histological grade in 50 meningiomas.
    Soon WC; Fountain DM; Koczyk K; Abdulla M; Giri S; Allinson K; Matys T; Guilfoyle MR; Kirollos RW; Santarius T
    Acta Neurochir (Wien); 2017 Nov; 159(11):2169-2177. PubMed ID: 28791500
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.
    Kang H; Witanto JN; Pratama K; Lee D; Choi KS; Choi SH; Kim KM; Kim MS; Kim JW; Kim YH; Park SJ; Park CK
    J Magn Reson Imaging; 2023 Mar; 57(3):871-881. PubMed ID: 35775971
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Association of apparent diffusion coefficient with Ki-67 proliferation index, progesterone-receptor status and various histopathological parameters, and its utility in predicting the high grade in meningiomas.
    Bozdağ M; Er A; Ekmekçi S
    Acta Radiol; 2021 Mar; 62(3):401-413. PubMed ID: 32397733
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Machine Learning Model Based on Unsupervised Clustering Multihabitat to Predict the Pathological Grading of Meningiomas.
    Wang X; Li J; Sun J; Liu W; Cai L; Zhao P; Yang Z; Lv H; Wang Z
    Biomed Res Int; 2022; 2022():8955227. PubMed ID: 36132071
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting meningioma grades and pathologic marker expression via deep learning.
    Chen J; Xue Y; Ren L; Lv K; Du P; Cheng H; Sun S; Hua L; Xie Q; Wu R; Gong Y
    Eur Radiol; 2024 May; 34(5):2997-3008. PubMed ID: 37853176
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A deep learning radiomics model may help to improve the prediction performance of preoperative grading in meningioma.
    Yang L; Xu P; Zhang Y; Cui N; Wang M; Peng M; Gao C; Wang T
    Neuroradiology; 2022 Jul; 64(7):1373-1382. PubMed ID: 35037985
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A deep learning radiomics model for preoperative grading in meningioma.
    Zhu Y; Man C; Gong L; Dong D; Yu X; Wang S; Fang M; Wang S; Fang X; Chen X; Tian J
    Eur J Radiol; 2019 Jul; 116():128-134. PubMed ID: 31153553
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Presurgical detection of brain invasion status in meningiomas based on first-order histogram based texture analysis of contrast enhanced imaging.
    Kandemirli SG; Chopra S; Priya S; Ward C; Locke T; Soni N; Srivastava S; Jones K; Bathla G
    Clin Neurol Neurosurg; 2020 Nov; 198():106205. PubMed ID: 32932028
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Molecular imaging correlates of tryptophan metabolism via the kynurenine pathway in human meningiomas.
    Bosnyák E; Kamson DO; Guastella AR; Varadarajan K; Robinette NL; Kupsky WJ; Muzik O; Michelhaugh SK; Mittal S; Juhász C
    Neuro Oncol; 2015 Sep; 17(9):1284-92. PubMed ID: 26092774
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.
    Hu J; Zhao Y; Li M; Liu J; Wang F; Weng Q; Wang X; Cao D
    Eur J Radiol; 2020 Oct; 131():109251. PubMed ID: 32916409
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.