164 related articles for article (PubMed ID: 28450707)
1. Post-Surgery Glioma Growth Modeling from Magnetic Resonance Images for Patients with Treatment.
Elazab A; Bai H; Abdulazeem YM; Abdelhamid T; Zhou S; Wong KKL; Hu Q
Sci Rep; 2017 Apr; 7(1):1222. PubMed ID: 28450707
[TBL] [Abstract][Full Text] [Related]
2. Low grade glioma growth modeling considering chemotherapy and radiotherapy effects from magnetic resonance images.
Elazab A; Hongmin Bai ; Xiaodong Zhang ; Qingmao Hu
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():3077-3080. PubMed ID: 29060548
[TBL] [Abstract][Full Text] [Related]
3. Modeling of glioma growth using modified reaction-diffusion equation on brain MR images.
Zhang Y; Liu PX; Hou W
Comput Methods Programs Biomed; 2022 Dec; 227():107233. PubMed ID: 36375418
[TBL] [Abstract][Full Text] [Related]
4. Brain glioma growth model using reaction-diffusion equation with viscous stress tensor on brain MR images.
Yuan J; Liu L
Magn Reson Imaging; 2016 Feb; 34(2):114-9. PubMed ID: 26518060
[TBL] [Abstract][Full Text] [Related]
5. Introduction of a standardized multimodality image protocol for navigation-guided surgery of suspected low-grade gliomas.
Mert A; Kiesel B; Wöhrer A; Martínez-Moreno M; Minchev G; Furtner J; Knosp E; Wolfsberger S; Widhalm G
Neurosurg Focus; 2015 Jan; 38(1):E4. PubMed ID: 25552284
[TBL] [Abstract][Full Text] [Related]
6. A Coupled Modified Reaction Diffusion and Biomechanical Models for Cerebral Tumor Growth Modeling in Presence of Treatment.
Elazab A; Bai H; Yang M; Hu Q; Le MH; Wang T; Lei B
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():758-761. PubMed ID: 30440506
[TBL] [Abstract][Full Text] [Related]
7. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs.
Tang F; Liang S; Zhong T; Huang X; Deng X; Zhang Y; Zhou L
Eur Radiol; 2020 Feb; 30(2):823-832. PubMed ID: 31650265
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Semi-automated segmentation of pre-operative low grade gliomas in magnetic resonance imaging.
Akkus Z; Sedlar J; Coufalova L; Korfiatis P; Kline TL; Warner JD; Agrawal J; Erickson BJ
Cancer Imaging; 2015 Aug; 15(1):12. PubMed ID: 26268363
[TBL] [Abstract][Full Text] [Related]
10. Modeling glioma growth and mass effect in 3D MR images of the brain.
Hogea C; Davatzikos C; Biros G
Med Image Comput Comput Assist Interv; 2007; 10(Pt 1):642-50. PubMed ID: 18051113
[TBL] [Abstract][Full Text] [Related]
11. Metabolic approach for tumor delineation in glioma surgery: 3D MR spectroscopy image-guided resection.
Zhang J; Zhuang DX; Yao CJ; Lin CP; Wang TL; Qin ZY; Wu JS
J Neurosurg; 2016 Jun; 124(6):1585-93. PubMed ID: 26636387
[TBL] [Abstract][Full Text] [Related]
12. Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.
Sauwen N; Acou M; Van Cauter S; Sima DM; Veraart J; Maes F; Himmelreich U; Achten E; Van Huffel S
Neuroimage Clin; 2016; 12():753-764. PubMed ID: 27812502
[TBL] [Abstract][Full Text] [Related]
13. Hierarchical non-negative matrix factorization to characterize brain tumor heterogeneity using multi-parametric MRI.
Sauwen N; Sima DM; Van Cauter S; Veraart J; Leemans A; Maes F; Himmelreich U; Van Huffel S
NMR Biomed; 2015 Dec; 28(12):1599-624. PubMed ID: 26458729
[TBL] [Abstract][Full Text] [Related]
14. Simulating radiotherapy effect in high-grade glioma by using diffusive modeling and brain atlases.
Roniotis A; Marias K; Sakkalis V; Manikis GC; Zervakis M
J Biomed Biotechnol; 2012; 2012():715812. PubMed ID: 23093856
[TBL] [Abstract][Full Text] [Related]
15. Radiotherapy of high-grade gliomas: current standards and new concepts, innovations in imaging and radiotherapy, and new therapeutic approaches.
Dhermain F
Chin J Cancer; 2014 Jan; 33(1):16-24. PubMed ID: 24384237
[TBL] [Abstract][Full Text] [Related]
16. An image-driven parameter estimation problem for a reaction-diffusion glioma growth model with mass effects.
Hogea C; Davatzikos C; Biros G
J Math Biol; 2008 Jun; 56(6):793-825. PubMed ID: 18026731
[TBL] [Abstract][Full Text] [Related]
17. Data-driven grading of brain gliomas: a multiparametric MR imaging study.
Caulo M; Panara V; Tortora D; Mattei PA; Briganti C; Pravatà E; Salice S; Cotroneo AR; Tartaro A
Radiology; 2014 Aug; 272(2):494-503. PubMed ID: 24661247
[TBL] [Abstract][Full Text] [Related]
18. Measurements of diagnostic examination performance using quantitative apparent diffusion coefficient and proton MR spectroscopic imaging in the preoperative evaluation of tumor grade in cerebral gliomas.
Server A; Kulle B; Gadmar ØB; Josefsen R; Kumar T; Nakstad PH
Eur J Radiol; 2011 Nov; 80(2):462-70. PubMed ID: 20708868
[TBL] [Abstract][Full Text] [Related]
19. Predicting in vivo glioma growth with the reaction diffusion equation constrained by quantitative magnetic resonance imaging data.
Hormuth DA; Weis JA; Barnes SL; Miga MI; Rericha EC; Quaranta V; Yankeelov TE
Phys Biol; 2015 Jun; 12(4):046006. PubMed ID: 26040472
[TBL] [Abstract][Full Text] [Related]
20. Magnetic resonance imaging evaluation of brain glioma before postoperative radiotherapy.
Sui Z; Zhang X; Li H; Xu D; Li G
Clin Transl Oncol; 2021 Apr; 23(4):820-826. PubMed ID: 32857338
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
