398 related articles for article (PubMed ID: 35111644)
1. Developing and validating a deep learning and radiomic model for glioma grading using multiplanar reconstructed magnetic resonance contrast-enhanced T1-weighted imaging: a robust, multi-institutional study.
Ding J; Zhao R; Qiu Q; Chen J; Duan J; Cao X; Yin Y
Quant Imaging Med Surg; 2022 Feb; 12(2):1517-1528. PubMed ID: 35111644
[TBL] [Abstract][Full Text] [Related]
2. Radiomics strategy for glioma grading using texture features from multiparametric MRI.
Tian Q; Yan LF; Zhang X; Zhang X; Hu YC; Han Y; Liu ZC; Nan HY; Sun Q; Sun YZ; Yang Y; Yu Y; Zhang J; Hu B; Xiao G; Chen P; Tian S; Xu J; Wang W; Cui GB
J Magn Reson Imaging; 2018 Dec; 48(6):1518-1528. PubMed ID: 29573085
[TBL] [Abstract][Full Text] [Related]
3. MRI-based intratumoral and peritumoral radiomics for preoperative prediction of glioma grade: a multicenter study.
Tan R; Sui C; Wang C; Zhu T
Front Oncol; 2024; 14():1401977. PubMed ID: 38803534
[TBL] [Abstract][Full Text] [Related]
4. Classification of the glioma grading using radiomics analysis.
Cho HH; Lee SH; Kim J; Park H
PeerJ; 2018; 6():e5982. PubMed ID: 30498643
[TBL] [Abstract][Full Text] [Related]
5. Radiomics MRI Phenotyping with Machine Learning to Predict the Grade of Lower-Grade Gliomas: A Study Focused on Nonenhancing Tumors.
Park YW; Choi YS; Ahn SS; Chang JH; Kim SH; Lee SK
Korean J Radiol; 2019 Sep; 20(9):1381-1389. PubMed ID: 31464116
[TBL] [Abstract][Full Text] [Related]
6. Multi-modal magnetic resonance imaging-based grading analysis for gliomas by integrating radiomics and deep features.
Ning Z; Luo J; Xiao Q; Cai L; Chen Y; Yu X; Wang J; Zhang Y
Ann Transl Med; 2021 Feb; 9(4):298. PubMed ID: 33708925
[TBL] [Abstract][Full Text] [Related]
7. Machine-Learning-Based Radiomics for Classifying Glioma Grade from Magnetic Resonance Images of the Brain.
Kumar A; Jha AK; Agarwal JP; Yadav M; Badhe S; Sahay A; Epari S; Sahu A; Bhattacharya K; Chatterjee A; Ganeshan B; Rangarajan V; Moyiadi A; Gupta T; Goda JS
J Pers Med; 2023 May; 13(6):. PubMed ID: 37373909
[TBL] [Abstract][Full Text] [Related]
8. Deriving quantitative information from multiparametric MRI via Radiomics: Evaluation of the robustness and predictive value of radiomic features in the discrimination of low-grade versus high-grade gliomas with machine learning.
Ubaldi L; Saponaro S; Giuliano A; Talamonti C; Retico A
Phys Med; 2023 Mar; 107():102538. PubMed ID: 36796177
[TBL] [Abstract][Full Text] [Related]
9. Thin-Slice Magnetic Resonance Imaging-Based Radiomics Signature Predicts Chromosomal 1p/19q Co-deletion Status in Grade II and III Gliomas.
Kong Z; Jiang C; Zhang Y; Liu S; Liu D; Liu Z; Chen W; Liu P; Yang T; Lyu Y; Zhao D; You H; Wang Y; Ma W; Feng F
Front Neurol; 2020; 11():551771. PubMed ID: 33192984
[No Abstract] [Full Text] [Related]
10. Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas.
Jiang C; Kong Z; Liu S; Feng S; Zhang Y; Zhu R; Chen W; Wang Y; Lyu Y; You H; Zhao D; Wang R; Wang Y; Ma W; Feng F
Eur J Radiol; 2019 Dec; 121():108714. PubMed ID: 31704598
[TBL] [Abstract][Full Text] [Related]
11. Radiomics-Based Machine Learning Classification for Glioma Grading Using Diffusion- and Perfusion-Weighted Magnetic Resonance Imaging.
Hashido T; Saito S; Ishida T
J Comput Assist Tomogr; 2021 Jul-Aug 01; 45(4):606-613. PubMed ID: 34270479
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. The combination of radiomics features and VASARI standard to predict glioma grade.
You W; Mao Y; Jiao X; Wang D; Liu J; Lei P; Liao W
Front Oncol; 2023; 13():1083216. PubMed ID: 37035137
[TBL] [Abstract][Full Text] [Related]
14. Considerable effects of imaging sequences, feature extraction, feature selection, and classifiers on radiomics-based prediction of microvascular invasion in hepatocellular carcinoma using magnetic resonance imaging.
Dai H; Lu M; Huang B; Tang M; Pang T; Liao B; Cai H; Huang M; Zhou Y; Chen X; Ding H; Feng ST
Quant Imaging Med Surg; 2021 May; 11(5):1836-1853. PubMed ID: 33936969
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Deep learning and machine learning predictive models for neurological function after interventional embolization of intracranial aneurysms.
Peng Y; Wang Y; Wen Z; Xiang H; Guo L; Su L; He Y; Pang H; Zhou P; Zhan X
Front Neurol; 2024; 15():1321923. PubMed ID: 38327618
[TBL] [Abstract][Full Text] [Related]
17. Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis.
Nakamoto T; Takahashi W; Haga A; Takahashi S; Kiryu S; Nawa K; Ohta T; Ozaki S; Nozawa Y; Tanaka S; Mukasa A; Nakagawa K
Sci Rep; 2019 Dec; 9(1):19411. PubMed ID: 31857632
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Deep Convolutional Radiomic Features on Diffusion Tensor Images for Classification of Glioma Grades.
Zhang Z; Xiao J; Wu S; Lv F; Gong J; Jiang L; Yu R; Luo T
J Digit Imaging; 2020 Aug; 33(4):826-837. PubMed ID: 32040669
[TBL] [Abstract][Full Text] [Related]
20. Conventional magnetic resonance imaging-based radiomic signature predicts telomerase reverse transcriptase promoter mutation status in grade II and III gliomas.
Jiang C; Kong Z; Zhang Y; Liu S; Liu Z; Chen W; Liu P; Liu D; Wang Y; Lyu Y; Zhao D; Wang Y; You H; Feng F; Ma W
Neuroradiology; 2020 Jul; 62(7):803-813. PubMed ID: 32239241
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]