188 related articles for article (PubMed ID: 37528895)
1. Fractal dimension: analyzing its potential as a neuroimaging biomarker for brain tumor diagnosis using machine learning.
Battalapalli D; Vidyadharan S; Prabhakar Rao BVVSN; Yogeeswari P; Kesavadas C; Rajagopalan V
Front Physiol; 2023; 14():1201617. PubMed ID: 37528895
[No Abstract] [Full Text] [Related]
2. Deep Learning Classifies Low- and High-Grade Glioma Patients with High Accuracy, Sensitivity, and Specificity Based on Their Brain White Matter Networks Derived from Diffusion Tensor Imaging.
Vidyadharan S; Prabhakar Rao BVVSN; Perumal Y; Chandrasekharan K; Rajagopalan V
Diagnostics (Basel); 2022 Dec; 12(12):. PubMed ID: 36553224
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Magnetic resonance perfusion for differentiating low-grade from high-grade gliomas at first presentation.
Abrigo JM; Fountain DM; Provenzale JM; Law EK; Kwong JS; Hart MG; Tam WWS
Cochrane Database Syst Rev; 2018 Jan; 1(1):CD011551. PubMed ID: 29357120
[TBL] [Abstract][Full Text] [Related]
5. Combining MRI and Histologic Imaging Features for Predicting Overall Survival in Patients with Glioma.
Rathore S; Chaddad A; Iftikhar MA; Bilello M; Abdulkadir A
Radiol Imaging Cancer; 2021 Jul; 3(4):e200108. PubMed ID: 34296969
[TBL] [Abstract][Full Text] [Related]
6. Grading of Gliomas by Contrast-Enhanced CT Radiomics Features.
Maskani M; Abbasi S; Etemad-Rezaee H; Abdolahi H; Zamanpour A; Montazerabadi A
J Biomed Phys Eng; 2024 Apr; 14(2):151-158. PubMed ID: 38628893
[TBL] [Abstract][Full Text] [Related]
7. Texture analysis of apparent diffusion coefficient (ADC) map for glioma grading: Analysis of whole tumoral and peri-tumoral tissue.
Soliman RK; Essa AA; Elhakeem AAS; Gamal SA; Zaitoun MMA
Diagn Interv Imaging; 2021 May; 102(5):287-295. PubMed ID: 33419692
[TBL] [Abstract][Full Text] [Related]
8. Monoexponential, biexponential and stretched exponential models of diffusion weighted magnetic resonance imaging in glioma in relation to histopathologic grade and Ki-67 labeling index using high B values.
Chaudhary N; Zhang G; Li S; Zhu W
Am J Transl Res; 2021; 13(11):12480-12494. PubMed ID: 34956467
[TBL] [Abstract][Full Text] [Related]
9. Diagnostic performance of 18F-FET PET in newly diagnosed cerebral lesions suggestive of glioma.
Rapp M; Heinzel A; Galldiks N; Stoffels G; Felsberg J; Ewelt C; Sabel M; Steiger HJ; Reifenberger G; Beez T; Coenen HH; Floeth FW; Langen KJ
J Nucl Med; 2013 Feb; 54(2):229-35. PubMed ID: 23232275
[TBL] [Abstract][Full Text] [Related]
10. Diagnostic performance of texture analysis on MRI in grading cerebral gliomas.
Skogen K; Schulz A; Dormagen JB; Ganeshan B; Helseth E; Server A
Eur J Radiol; 2016 Apr; 85(4):824-9. PubMed ID: 26971430
[TBL] [Abstract][Full Text] [Related]
11. A comparative study for glioma classification using deep convolutional neural networks.
Özcan H; Emiroğlu BG; Sabuncuoğlu H; Özdoğan S; Soyer A; Saygı T
Math Biosci Eng; 2021 Jan; 18(2):1550-1572. PubMed ID: 33757198
[TBL] [Abstract][Full Text] [Related]
12. The diagnostic value of quantitative texture analysis of conventional MRI sequences using artificial neural networks in grading gliomas.
Alis D; Bagcilar O; Senli YD; Isler C; Yergin M; Kocer N; Islak C; Kizilkilic O
Clin Radiol; 2020 May; 75(5):351-357. PubMed ID: 31973941
[TBL] [Abstract][Full Text] [Related]
13. Efficacy of three-dimensional arterial spin labeling and how it compares against that of contrast enhanced magnetic resonance imaging in preoperative grading of brain gliomas.
Wang K; Guo H; Tian X; Miao Y; Han P; Jin F
Environ Toxicol; 2023 Jul; 38(7):1723-1731. PubMed ID: 37040330
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Brain Glioma Localization Diagnosis Based on Magnetic Resonance Imaging.
Jin Y; Peng H; Peng J
World Neurosurg; 2021 May; 149():325-332. PubMed ID: 32992057
[TBL] [Abstract][Full Text] [Related]
16. Diagnostic Accuracy of Machine Learning-Based Radiomics in Grading Gliomas: Systematic Review and Meta-Analysis.
Sohn CK; Bisdas S
Contrast Media Mol Imaging; 2020; 2020():2127062. PubMed ID: 33746649
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Multivoxel
Durmo F; Rydelius A; Cuellar Baena S; Askaner K; Lätt J; Bengzon J; Englund E; Chenevert TL; Björkman-Burtscher IM; Sundgren PC
Tomography; 2018 Dec; 4(4):172-181. PubMed ID: 30588503
[TBL] [Abstract][Full Text] [Related]
19. Glioma Grading via Analysis of Digital Pathology Images Using Machine Learning.
Rathore S; Niazi T; Iftikhar MA; Chaddad A
Cancers (Basel); 2020 Mar; 12(3):. PubMed ID: 32131409
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
