837 related articles for article (PubMed ID: 30443758)
1. 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]
2. Comparison of machine learning classifiers for differentiation of grade 1 from higher gradings in meningioma: A multicenter radiomics study.
Hamerla G; Meyer HJ; Schob S; Ginat DT; Altman A; Lim T; Gihr GA; Horvath-Rizea D; Hoffmann KT; Surov A
Magn Reson Imaging; 2019 Nov; 63():244-249. PubMed ID: 31425811
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Accuracy of Radiomics-Based Feature Analysis on Multiparametric Magnetic Resonance Images for Noninvasive Meningioma Grading.
Laukamp KR; Shakirin G; Baeßler B; Thiele F; Zopfs D; Große Hokamp N; Timmer M; Kabbasch C; Perkuhn M; Borggrefe J
World Neurosurg; 2019 Dec; 132():e366-e390. PubMed ID: 31476455
[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. Histogram analysis in predicting the grade and histological subtype of meningiomas based on diffusion kurtosis imaging.
Chen X; Lin L; Wu J; Yang G; Zhong T; Du X; Chen Z; Xu G; Song Y; Xue Y; Duan Q
Acta Radiol; 2020 Sep; 61(9):1228-1239. PubMed ID: 31986895
[TBL] [Abstract][Full Text] [Related]
7. The diagnostic value of using combined MR diffusion tensor imaging parameters to differentiate between low- and high-grade meningioma.
Aslan K; Gunbey HP; Tomak L; Incesu L
Br J Radiol; 2018 Jul; 91(1088):20180088. PubMed ID: 29770735
[TBL] [Abstract][Full Text] [Related]
8. Determination of grade and subtype of meningiomas by using histogram analysis of diffusion-tensor imaging metrics.
Wang S; Kim S; Zhang Y; Wang L; Lee EB; Syre P; Poptani H; Melhem ER; Lee JY
Radiology; 2012 Feb; 262(2):584-92. PubMed ID: 22084207
[TBL] [Abstract][Full Text] [Related]
9. The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest.
Lu Y; Liu L; Luan S; Xiong J; Geng D; Yin B
Eur Radiol; 2019 Mar; 29(3):1318-1328. PubMed ID: 30088065
[TBL] [Abstract][Full Text] [Related]
10. Role of diffusion tensor imaging in differentiating subtypes of meningiomas.
Jolapara M; Kesavadas C; Radhakrishnan VV; Thomas B; Gupta AK; Bodhey N; Patro S; Saini J; George U; Sarma PS
J Neuroradiol; 2010 Dec; 37(5):277-83. PubMed ID: 20381865
[TBL] [Abstract][Full Text] [Related]
11. The role of diffusion tensor imaging and dynamic susceptibility perfusion MRI in the evaluation of meningioma grade and subtype.
Zikou A; Alexiou GA; Goussia A; Kosta P; Xydis V; Voulgaris S; Kyritsis AP; Argyropoulou MI
Clin Neurol Neurosurg; 2016 Jul; 146():109-15. PubMed ID: 27208870
[TBL] [Abstract][Full Text] [Related]
12. Meningiomas: Preoperative predictive histopathological grading based on radiomics of MRI.
Han Y; Wang T; Wu P; Zhang H; Chen H; Yang C
Magn Reson Imaging; 2021 Apr; 77():36-43. PubMed ID: 33220449
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Role of MR Morphology and Diffusion-Weighted Imaging in the Evaluation of Meningiomas: Radio-Pathologic Correlation.
Ranabhat K; Bishokarma S; Agrawal P; Shrestha P; Panth R; Ghimire RK
JNMA J Nepal Med Assoc; 2019; 57(215):37-44. PubMed ID: 31080244
[TBL] [Abstract][Full Text] [Related]
15. Comparative Analysis of Diffusional Kurtosis Imaging, Diffusion Tensor Imaging, and Diffusion-Weighted Imaging in Grading and Assessing Cellular Proliferation of Meningiomas.
Lin L; Bhawana R; Xue Y; Duan Q; Jiang R; Chen H; Chen X; Sun B; Lin H
AJNR Am J Neuroradiol; 2018 Jun; 39(6):1032-1038. PubMed ID: 29748203
[TBL] [Abstract][Full Text] [Related]
16. Multi-parametric MRI-based machine learning model for prediction of WHO grading in patients with meningiomas.
Zhao Z; Nie C; Zhao L; Xiao D; Zheng J; Zhang H; Yan P; Jiang X; Zhao H
Eur Radiol; 2024 Apr; 34(4):2468-2479. PubMed ID: 37812296
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Prediction of meningioma grade by constructing a clinical radiomics model nomogram based on magnetic resonance imaging.
Han T; Liu X; Long C; Xu Z; Geng Y; Zhang B; Deng L; Jing M; Zhou J
Magn Reson Imaging; 2023 Dec; 104():16-22. PubMed ID: 37734573
[TBL] [Abstract][Full Text] [Related]
19. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading.
Inano R; Oishi N; Kunieda T; Arakawa Y; Yamao Y; Shibata S; Kikuchi T; Fukuyama H; Miyamoto S
Neuroimage Clin; 2014; 5():396-407. PubMed ID: 25180159
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
