256 related articles for article (PubMed ID: 29145421)
1. Radiographic prediction of meningioma grade by semantic and radiomic features.
Coroller TP; Bi WL; Huynh E; Abedalthagafi M; Aizer AA; Greenwald NF; Parmar C; Narayan V; Wu WW; Miranda de Moura S; Gupta S; Beroukhim R; Wen PY; Al-Mefty O; Dunn IF; Santagata S; Alexander BM; Huang RY; Aerts HJWL
PLoS One; 2017; 12(11):e0187908. PubMed ID: 29145421
[TBL] [Abstract][Full Text] [Related]
2. MRI-based machine learning models predict the malignant biological behavior of meningioma.
Li M; Liu L; Qi J; Qiao Y; Zeng H; Jiang W; Zhu R; Chen F; Huang H; Wu S
BMC Med Imaging; 2023 Sep; 23(1):141. PubMed ID: 37759192
[TBL] [Abstract][Full Text] [Related]
3. Meningioma Consistency Can Be Defined by Combining the Radiomic Features of Magnetic Resonance Imaging and Ultrasound Elastography. A Pilot Study Using Machine Learning Classifiers.
Cepeda S; Arrese I; García-García S; Velasco-Casares M; Escudero-Caro T; Zamora T; Sarabia R
World Neurosurg; 2021 Feb; 146():e1147-e1159. PubMed ID: 33259973
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
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. Machine learning analyses can differentiate meningioma grade by features on magnetic resonance imaging.
Hale AT; Stonko DP; Wang L; Strother MK; Chambless LB
Neurosurg Focus; 2018 Nov; 45(5):E4. PubMed ID: 30453458
[TBL] [Abstract][Full Text] [Related]
8. Changes in radiomic and radiologic features in meningiomas after radiation therapy.
Jo SW; Kim ES; Yoon DY; Kwon MJ
BMC Med Imaging; 2023 Oct; 23(1):164. PubMed ID: 37858048
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. The Role of Pre-Operative MRI for Prediction of High-Grade Intracranial Meningioma: A Retrospective Study.
Radeesri K; Lekhavat V
Asian Pac J Cancer Prev; 2023 Mar; 24(3):819-825. PubMed ID: 36974533
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Radiomic Features of the Edema Region May Contribute to Grading Meningiomas With Peritumoral Edema.
Guo Z; Tian Z; Shi F; Xu P; Zhang J; Ling C; Zeng Q
J Magn Reson Imaging; 2023 Jul; 58(1):301-310. PubMed ID: 36259547
[TBL] [Abstract][Full Text] [Related]
13. Radiomic Analysis of Craniopharyngioma and Meningioma in the Sellar/Parasellar Area with MR Images Features and Texture Features: A Feasible Study.
Tian Z; Chen C; Zhang Y; Fan Y; Feng R; Xu J
Contrast Media Mol Imaging; 2020; 2020():4837156. PubMed ID: 32158365
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study.
Zhang J; Yao K; Liu P; Liu Z; Han T; Zhao Z; Cao Y; Zhang G; Zhang J; Tian J; Zhou J
EBioMedicine; 2020 Aug; 58():102933. PubMed ID: 32739863
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. 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]
18. Prediction of High-Grade Pediatric Meningiomas: Magnetic Resonance Imaging Features Based on T1-Weighted, T2-Weighted, and Contrast-Enhanced T1-Weighted Images.
Li H; Zhao M; Jiao Y; Ge P; Li Z; Ma J; Wang S; Cao Y; Zhao J
World Neurosurg; 2016 Jul; 91():89-95. PubMed ID: 27046015
[TBL] [Abstract][Full Text] [Related]
19. Dynamic susceptibility contrast and dynamic contrast-enhanced MRI characteristics to distinguish microcystic meningiomas from traditional Grade I meningiomas and high-grade gliomas.
Hussain NS; Moisi MD; Keogh B; McCullough BJ; Rostad S; Newell D; Gwinn R; Foltz G; Mayberg M; Aguedan B; Good V; Fouke SJ
J Neurosurg; 2017 Apr; 126(4):1220-1226. PubMed ID: 27285539
[TBL] [Abstract][Full Text] [Related]
20. Differentiating meningioma grade by imaging features on magnetic resonance imaging.
Hale AT; Wang L; Strother MK; Chambless LB
J Clin Neurosci; 2018 Feb; 48():71-75. PubMed ID: 29174756
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
