183 related articles for article (PubMed ID: 36453877)
1. Quantification of Radiomics features of Peritumoral Vasogenic Edema extracted from fluid-attenuated inversion recovery images in glioblastoma and isolated brain metastasis, using T1-dynamic contrast-enhanced Perfusion analysis.
Parvaze PS; Bhattacharjee R; Verma YK; Singh RK; Yadav V; Singh A; Khanna G; Ahlawat S; Trivedi R; Patir R; Vaishya S; Shah TJ; Gupta RK
NMR Biomed; 2023 May; 36(5):e4884. PubMed ID: 36453877
[TBL] [Abstract][Full Text] [Related]
2. Radiomics-based evaluation and possible characterization of dynamic contrast enhanced (DCE) perfusion derived different sub-regions of Glioblastoma.
Suhail Parvaze ; Bhattacharjee R; Singh A; Ahlawat S; Patir R; Vaishya S; Shah TJ; Gupta RK
Eur J Radiol; 2023 Feb; 159():110655. PubMed ID: 36577183
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Differentiation between vasogenic-edema versus tumor-infiltrative area in patients with glioblastoma during bevacizumab therapy: a longitudinal MRI study.
Artzi M; Bokstein F; Blumenthal DT; Aizenstein O; Liberman G; Corn BW; Ben Bashat D
Eur J Radiol; 2014 Jul; 83(7):1250-1256. PubMed ID: 24809637
[TBL] [Abstract][Full Text] [Related]
5. Glioblastomas with and without peritumoral fluid-attenuated inversion recovery (FLAIR) hyperintensity present morphological and microstructural differences on conventional MR images.
Han Q; Lu Y; Wang D; Li X; Ruan Z; Mei N; Ji X; Geng D; Yin B
Eur Radiol; 2023 Dec; 33(12):9139-9151. PubMed ID: 37495706
[TBL] [Abstract][Full Text] [Related]
6. Radiomics features to distinguish glioblastoma from primary central nervous system lymphoma on multi-parametric MRI.
Kim Y; Cho HH; Kim ST; Park H; Nam D; Kong DS
Neuroradiology; 2018 Dec; 60(12):1297-1305. PubMed ID: 30232517
[TBL] [Abstract][Full Text] [Related]
7. Robust texture features for response monitoring of glioblastoma multiforme on T1-weighted and T2-FLAIR MR images: a preliminary investigation in terms of identification and segmentation.
Assefa D; Keller H; Ménard C; Laperriere N; Ferrari RJ; Yeung I
Med Phys; 2010 Apr; 37(4):1722-36. PubMed ID: 20443493
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Extensive peritumoral edema and brain-to-tumor interface MRI features enable prediction of brain invasion in meningioma: development and validation.
Joo L; Park JE; Park SY; Nam SJ; Kim YH; Kim JH; Kim HS
Neuro Oncol; 2021 Feb; 23(2):324-333. PubMed ID: 32789495
[TBL] [Abstract][Full Text] [Related]
10. Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis.
Artzi M; Bressler I; Ben Bashat D
J Magn Reson Imaging; 2019 Aug; 50(2):519-528. PubMed ID: 30635952
[TBL] [Abstract][Full Text] [Related]
11. Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation.
Cheong EN; Park JE; Park SY; Jung SC; Kim HS
Eur Radiol; 2024 Mar; 34(3):2008-2023. PubMed ID: 37665391
[TBL] [Abstract][Full Text] [Related]
12. On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.
Sengupta A; Agarwal S; Gupta PK; Ahlawat S; Patir R; Gupta RK; Singh A
Eur J Radiol; 2018 Sep; 106():199-208. PubMed ID: 30150045
[TBL] [Abstract][Full Text] [Related]
13. An integrative non-invasive malignant brain tumors classification and Ki-67 labeling index prediction pipeline with radiomics approach.
Zhang L; Liu X; Xu X; Liu W; Jia Y; Chen W; Fu X; Li Q; Sun X; Zhang Y; Shu S; Zhang X; Xiang R; Chen H; Sun P; Geng D; Yu Z; Liu J; Wang J
Eur J Radiol; 2023 Jan; 158():110639. PubMed ID: 36463703
[TBL] [Abstract][Full Text] [Related]
14. Quantitative mapping of individual voxels in the peritumoral region of IDH-wildtype glioblastoma to distinguish between tumor infiltration and edema.
Dasgupta A; Geraghty B; Maralani PJ; Malik N; Sandhu M; Detsky J; Tseng CL; Soliman H; Myrehaug S; Husain Z; Perry J; Lau A; Sahgal A; Czarnota GJ
J Neurooncol; 2021 Jun; 153(2):251-261. PubMed ID: 33905055
[TBL] [Abstract][Full Text] [Related]
15. Differentiation of Pseudoprogression from True Progressionin Glioblastoma Patients after Standard Treatment: A Machine Learning Strategy Combinedwith Radiomics Features from T
Sun YZ; Yan LF; Han Y; Nan HY; Xiao G; Tian Q; Pu WH; Li ZY; Wei XC; Wang W; Cui GB
BMC Med Imaging; 2021 Feb; 21(1):17. PubMed ID: 33535988
[TBL] [Abstract][Full Text] [Related]
16. Glioblastomas and brain metastases differentiation following an MRI texture analysis-based radiomics approach.
Ortiz-Ramón R; Ruiz-España S; Mollá-Olmos E; Moratal D
Phys Med; 2020 Aug; 76():44-54. PubMed ID: 32593138
[TBL] [Abstract][Full Text] [Related]
17. Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach.
Suh HB; Choi YS; Bae S; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Lee SK
Eur Radiol; 2018 Sep; 28(9):3832-3839. PubMed ID: 29626238
[TBL] [Abstract][Full Text] [Related]
18. Multiparametric Magnetic Resonance Imaging in the Assessment of Primary Brain Tumors Through Radiomic Features: A Metric for Guided Radiation Treatment Planning.
Florez E; Nichols T; E Parker E; T Lirette S; Howard CM; Fatemi A
Cureus; 2018 Oct; 10(10):e3426. PubMed ID: 30542636
[TBL] [Abstract][Full Text] [Related]
19. Differentiation of Glioblastoma and Solitary Brain Metastasis by Gradient of Relative Cerebral Blood Volume in the Peritumoral Brain Zone Derived from Dynamic Susceptibility Contrast Perfusion Magnetic Resonance Imaging.
She D; Xing Z; Cao D
J Comput Assist Tomogr; 2019; 43(1):13-17. PubMed ID: 30015801
[TBL] [Abstract][Full Text] [Related]
20. Physiological MRI Biomarkers in the Differentiation Between Glioblastomas and Solitary Brain Metastases.
Heynold E; Zimmermann M; Hore N; Buchfelder M; Doerfler A; Stadlbauer A; Kremenevski N
Mol Imaging Biol; 2021 Oct; 23(5):787-795. PubMed ID: 33891264
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]