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 *

766 related articles for article (PubMed ID: 33285357)

  • 1. Towards effective machine learning in medical imaging analysis: A novel approach and expert evaluation of high-grade glioma 'ground truth' simulation on MRI.
    Sepehri K; Song X; Proulx R; Hajra SG; Dobberthien B; Liu CC; D'Arcy RCN; Murray D; Krauze AV
    Int J Med Inform; 2021 Feb; 146():104348. PubMed ID: 33285357
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automated glioma grading on conventional MRI images using deep convolutional neural networks.
    Zhuge Y; Ning H; Mathen P; Cheng JY; Krauze AV; Camphausen K; Miller RW
    Med Phys; 2020 Jul; 47(7):3044-3053. PubMed ID: 32277478
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study.
    Kickingereder P; Isensee F; Tursunova I; Petersen J; Neuberger U; Bonekamp D; Brugnara G; Schell M; Kessler T; Foltyn M; Harting I; Sahm F; Prager M; Nowosielski M; Wick A; Nolden M; Radbruch A; Debus J; Schlemmer HP; Heiland S; Platten M; von Deimling A; van den Bent MJ; Gorlia T; Wick W; Bendszus M; Maier-Hein KH
    Lancet Oncol; 2019 May; 20(5):728-740. PubMed ID: 30952559
    [TBL] [Abstract][Full Text] [Related]  

  • 4. On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.
    Sengupta A; Agarwal S; Gupta PK; Ahlawat S; Patir R; Gupta RK; Singh A
    Eur J Radiol; 2018 Sep; 106():199-208. PubMed ID: 30150045
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.
    Zhang X; Yan LF; Hu YC; Li G; Yang Y; Han Y; Sun YZ; Liu ZC; Tian Q; Han ZY; Liu LD; Hu BQ; Qiu ZY; Wang W; Cui GB
    Oncotarget; 2017 Jul; 8(29):47816-47830. PubMed ID: 28599282
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine-learning in grading of gliomas based on multi-parametric magnetic resonance imaging at 3T.
    Citak-Er F; Firat Z; Kovanlikaya I; Ture U; Ozturk-Isik E
    Comput Biol Med; 2018 Aug; 99():154-160. PubMed ID: 29933126
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Glioma grading using a machine-learning framework based on optimized features obtained from T
    Sengupta A; Ramaniharan AK; Gupta RK; Agarwal S; Singh A
    J Magn Reson Imaging; 2019 Oct; 50(4):1295-1306. PubMed ID: 30895704
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI.
    Soltaninejad M; Yang G; Lambrou T; Allinson N; Jones TL; Barrick TR; Howe FA; Ye X
    Int J Comput Assist Radiol Surg; 2017 Feb; 12(2):183-203. PubMed ID: 27651330
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.
    De Looze C; Beausang A; Cryan J; Loftus T; Buckley PG; Farrell M; Looby S; Reilly R; Brett F; Kearney H
    J Neurooncol; 2018 Sep; 139(2):491-499. PubMed ID: 29770897
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics.
    Carré A; Klausner G; Edjlali M; Lerousseau M; Briend-Diop J; Sun R; Ammari S; Reuzé S; Alvarez Andres E; Estienne T; Niyoteka S; Battistella E; Vakalopoulou M; Dhermain F; Paragios N; Deutsch E; Oppenheim C; Pallud J; Robert C
    Sci Rep; 2020 Jul; 10(1):12340. PubMed ID: 32704007
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction.
    Choi YS; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Jain R; Lee SK
    Eur Radiol; 2020 Jul; 30(7):3834-3842. PubMed ID: 32162004
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review.
    Buchlak QD; Esmaili N; Leveque JC; Bennett C; Farrokhi F; Piccardi M
    J Clin Neurosci; 2021 Jul; 89():177-198. PubMed ID: 34119265
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.
    Sauwen N; Acou M; Sima DM; Veraart J; Maes F; Himmelreich U; Achten E; Huffel SV
    BMC Med Imaging; 2017 May; 17(1):29. PubMed ID: 28472943
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Imaging biomarker analysis of advanced multiparametric MRI for glioma grading.
    Vamvakas A; Williams SC; Theodorou K; Kapsalaki E; Fountas K; Kappas C; Vassiou K; Tsougos I
    Phys Med; 2019 Apr; 60():188-198. PubMed ID: 30910431
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Radiomics Analysis for Glioma Malignancy Evaluation Using Diffusion Kurtosis and Tensor Imaging.
    Takahashi S; Takahashi W; Tanaka S; Haga A; Nakamoto T; Suzuki Y; Mukasa A; Takayanagi S; Kitagawa Y; Hana T; Nejo T; Nomura M; Nakagawa K; Saito N
    Int J Radiat Oncol Biol Phys; 2019 Nov; 105(4):784-791. PubMed ID: 31344432
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Grading of gliomas using transfer learning on MRI images.
    Fasihi Shirehjini O; Babapour Mofrad F; Shahmohammadi M; Karami F
    MAGMA; 2023 Feb; 36(1):43-53. PubMed ID: 36326937
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Radiogenomics of lower-grade gliomas: machine learning-based MRI texture analysis for predicting 1p/19q codeletion status.
    Kocak B; Durmaz ES; Ates E; Sel I; Turgut Gunes S; Kaya OK; Zeynalova A; Kilickesmez O
    Eur Radiol; 2020 Feb; 30(2):877-886. PubMed ID: 31691122
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.
    Sauwen N; Acou M; Van Cauter S; Sima DM; Veraart J; Maes F; Himmelreich U; Achten E; Van Huffel S
    Neuroimage Clin; 2016; 12():753-764. PubMed ID: 27812502
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Segmenting pediatric optic pathway gliomas from MRI using deep learning.
    Nalepa J; Adamski S; Kotowski K; Chelstowska S; Machnikowska-Sokolowska M; Bozek O; Wisz A; Jurkiewicz E
    Comput Biol Med; 2022 Mar; 142():105237. PubMed ID: 35074737
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Classification of High-Grade Glioma into Tumor and Nontumor Components Using Support Vector Machine.
    Blumenthal DT; Artzi M; Liberman G; Bokstein F; Aizenstein O; Ben Bashat D
    AJNR Am J Neuroradiol; 2017 May; 38(5):908-914. PubMed ID: 28385884
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 39.