594 related articles for article (PubMed ID: 31476455)
1. 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]
2. 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]
3. 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]
4. 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]
5. 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]
6. Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping.
Zhang S; Chiang GC; Knapp JM; Zecca CM; He D; Ramakrishna R; Magge RS; Pisapia DJ; Fine HA; Tsiouris AJ; Zhao Y; Heier LA; Wang Y; Kovanlikaya I
J Neuroradiol; 2020 Jun; 47(4):272-277. PubMed ID: 31136748
[TBL] [Abstract][Full Text] [Related]
7. Radiomics analysis of multiparametric MRI for the preoperative evaluation of pathological grade in bladder cancer tumors.
Wang H; Hu D; Yao H; Chen M; Li S; Chen H; Luo J; Feng Y; Guo Y
Eur Radiol; 2019 Nov; 29(11):6182-6190. PubMed ID: 31016445
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. Multiparameter MRI-based radiomics nomogram for preoperative prediction of brain invasion in atypical meningioma:a multicentre study.
Yu J; Kong X; Xie D; Zheng F; Wang C; Shi D; He C; Liang X; Xu H; Li S; Chen X
BMC Med Imaging; 2024 Jun; 24(1):134. PubMed ID: 38840054
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Multi-parametric qualitative and quantitative MRI assessment as predictor of histological grading in previously treated meningiomas.
Sacco S; Ballati F; Gaetani C; Lomoro P; Farina LM; Bacila A; Imparato S; Paganelli C; Buizza G; Iannalfi A; Baroni G; Valvo F; Bastianello S; Preda L
Neuroradiology; 2020 Nov; 62(11):1441-1449. PubMed ID: 32583368
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Development of a Clinicopathological-Radiomics Model for Predicting Progression and Recurrence in Meningioma Patients.
He M; Wang X; Huang C; Peng X; Li N; Li F; Dong H; Wang Z; Zhao L; Wu F; Zhang M; Guan X; Xu X
Acad Radiol; 2024 May; 31(5):2061-2073. PubMed ID: 37993304
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. MRI- and DWI-Based Radiomics Features for Preoperatively Predicting Meningioma Sinus Invasion.
Gui Y; Chen F; Ren J; Wang L; Chen K; Zhang J
J Imaging Inform Med; 2024 Jun; 37(3):1054-1066. PubMed ID: 38351221
[TBL] [Abstract][Full Text] [Related]
17. Evaluation parameters between intra-voxel incoherent motion and diffusion-weighted imaging in grading and differentiating histological subtypes of meningioma: A prospective pilot study.
Yiping L; Kawai S; Jianbo W; Li L; Daoying G; Bo Y
J Neurol Sci; 2017 Jan; 372():60-69. PubMed ID: 28017250
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Radiomics approach for prediction of recurrence in skull base meningiomas.
Zhang Y; Chen JH; Chen TY; Lim SW; Wu TC; Kuo YT; Ko CC; Su MY
Neuroradiology; 2019 Dec; 61(12):1355-1364. PubMed ID: 31324948
[TBL] [Abstract][Full Text] [Related]
20. Differentiation Researches on the Meningioma Subtypes by Radiomics from Contrast-Enhanced Magnetic Resonance Imaging: A Preliminary Study.
Niu L; Zhou X; Duan C; Zhao J; Sui Q; Liu X; Zhang X
World Neurosurg; 2019 Jun; 126():e646-e652. PubMed ID: 30831287
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
