254 related articles for article (PubMed ID: 25963601)
1. An inverse problem formulation for parameter estimation of a reaction-diffusion model of low grade gliomas.
Gholami A; Mang A; Biros G
J Math Biol; 2016 Jan; 72(1-2):409-33. PubMed ID: 25963601
[TBL] [Abstract][Full Text] [Related]
2. Mathematical modelling of glioma growth: the use of Diffusion Tensor Imaging (DTI) data to predict the anisotropic pathways of cancer invasion.
Painter KJ; Hillen T
J Theor Biol; 2013 Apr; 323():25-39. PubMed ID: 23376578
[TBL] [Abstract][Full Text] [Related]
3. Simulating PDGF-Driven Glioma Growth and Invasion in an Anatomically Accurate Brain Domain.
Massey SC; Rockne RC; Hawkins-Daarud A; Gallaher J; Anderson ARA; Canoll P; Swanson KR
Bull Math Biol; 2018 May; 80(5):1292-1309. PubMed ID: 28842831
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. Glioma follow white matter tracts: a multiscale DTI-based model.
Engwer C; Hillen T; Knappitsch M; Surulescu C
J Math Biol; 2015 Sep; 71(3):551-82. PubMed ID: 25212910
[TBL] [Abstract][Full Text] [Related]
7. Simulation of anisotropic growth of low-grade gliomas using diffusion tensor imaging.
Jbabdi S; Mandonnet E; Duffau H; Capelle L; Swanson KR; Pélégrini-Issac M; Guillevin R; Benali H
Magn Reson Med; 2005 Sep; 54(3):616-24. PubMed ID: 16088879
[TBL] [Abstract][Full Text] [Related]
8. High-grade glioma diffusive modeling using statistical tissue information and diffusion tensors extracted from atlases.
Roniotis A; Manikis GC; Sakkalis V; Zervakis ME; Karatzanis I; Marias K
IEEE Trans Inf Technol Biomed; 2012 Mar; 16(2):255-63. PubMed ID: 21990337
[TBL] [Abstract][Full Text] [Related]
9. A Patient-Specific Anisotropic Diffusion Model for Brain Tumour Spread.
Swan A; Hillen T; Bowman JC; Murtha AD
Bull Math Biol; 2018 May; 80(5):1259-1291. PubMed ID: 28493055
[TBL] [Abstract][Full Text] [Related]
10. Biophysical modeling of brain tumor progression: from unconditionally stable explicit time integration to an inverse problem with parabolic PDE constraints for model calibration.
Mang A; Toma A; Schuetz TA; Becker S; Eckey T; Mohr C; Petersen D; Buzug TM
Med Phys; 2012 Jul; 39(7):4444-59. PubMed ID: 22830777
[TBL] [Abstract][Full Text] [Related]
11. Estimating intratumoral heterogeneity from spatiotemporal data.
Rutter EM; Banks HT; Flores KB
J Math Biol; 2018 Dec; 77(6-7):1999-2022. PubMed ID: 29737395
[TBL] [Abstract][Full Text] [Related]
12. Tumor invasion margin on the Riemannian space of brain fibers.
Mosayebi P; Cobzas D; Murtha A; Jagersand M
Med Image Anal; 2012 Feb; 16(2):361-73. PubMed ID: 22154876
[TBL] [Abstract][Full Text] [Related]
13. Image guided personalization of reaction-diffusion type tumor growth models using modified anisotropic eikonal equations.
Konukoglu E; Clatz O; Menze BH; Stieltjes B; Weber MA; Mandonnet E; Delingette H; Ayache N
IEEE Trans Med Imaging; 2010 Jan; 29(1):77-95. PubMed ID: 19605320
[TBL] [Abstract][Full Text] [Related]
14. Analysis of diffusion tensor imaging metrics for gliomas grading at 3 T.
Server A; Graff BA; Josefsen R; Orheim TE; Schellhorn T; Nordhøy W; Nakstad PH
Eur J Radiol; 2014 Mar; 83(3):e156-65. PubMed ID: 24457139
[TBL] [Abstract][Full Text] [Related]
15. Mathematical modeling of efficient protocols to control glioma growth.
Branco JR; Ferreira JA; de Oliveira P
Math Biosci; 2014 Sep; 255():83-90. PubMed ID: 25057777
[TBL] [Abstract][Full Text] [Related]
16. Differentiation between low-grade and high-grade glioma using combined diffusion tensor imaging metrics.
Ma L; Song ZJ
Clin Neurol Neurosurg; 2013 Dec; 115(12):2489-95. PubMed ID: 24183513
[TBL] [Abstract][Full Text] [Related]
17. [Application of diffusion tensor imaging in preoperation and postoperation patients of glioma with 3.0 Tesla MRI].
Li X; Yu RT; Xu K; Li FC; Fan YC; Gao WC; Guo KQ; Pan X; Yang C
Zhonghua Yi Xue Za Zhi; 2009 May; 89(19):1300-4. PubMed ID: 19615179
[TBL] [Abstract][Full Text] [Related]
18. Volumetric assessment of tumor infiltration of adjacent white matter based on anatomic MRI and diffusion tensor tractography.
Talos IF; Zou KH; Kikinis R; Jolesz FA
Acad Radiol; 2007 Apr; 14(4):431-6. PubMed ID: 17368212
[TBL] [Abstract][Full Text] [Related]
19. Fast estimation of diffusion tensors under Rician noise by the EM algorithm.
Liu J; Gasbarra D; Railavo J
J Neurosci Methods; 2016 Jan; 257():147-58. PubMed ID: 26456357
[TBL] [Abstract][Full Text] [Related]
20. Extrapolating glioma invasion margin in brain magnetic resonance images: suggesting new irradiation margins.
Konukoglu E; Clatz O; Bondiau PY; Delingette H; Ayache N
Med Image Anal; 2010 Apr; 14(2):111-25. PubMed ID: 20042359
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
