Diffusion Tensor Imaging for Glioma Grading: Analysis of Fiber Density Index
Introduction: The most common primary tumors of brain are gliomas and tumor grading is essential for designing proper treatment strategies. The gold standard choice to determine grade of glial tumor is biopsy which is an invasive method. The purpose of this study was to investigatethe role of fiber...
Main Authors: | Fariba Davanian, Fariborz Faeghi, Sohrab Shahzadi, Zahra Farshifar |
---|---|
Format: | Article |
Language: | English |
Published: |
Iran University of Medical Sciences
2017-01-01
|
Series: | Basic and Clinical Neuroscience |
Subjects: | |
Online Access: | http://bcn.iums.ac.ir/browse.php?a_code=A-10-863-1&slc_lang=en&sid=1 |
Similar Items
-
Evaluation of the Role of Diffusion Tensor Imaging in Grading of Glial Tumors based on Relative Anisotropy
by: Fariba Davnian, et al.
Published: (2016-01-01) -
Analysis of DTI-Derived Tensor Metrics in Differential Diagnosis between Low-grade and High-grade Gliomas
by: Liang Jiang, et al.
Published: (2017-08-01) -
Accurate low and high grade glioma classification using free water eliminated diffusion tensor metrics and ensemble machine learning
by: Sreejith Vidyadharan, et al.
Published: (2024-08-01) -
Grading of Glioma Tumors by Analysis of Minimum Apparent Diffusion Coefficient and Maximum Relative Cerebral Blood Volume
by: Mahdiyeh Saberi, et al.
Published: (2016-03-01) -
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
by: Sreejith Vidyadharan, et al.
Published: (2022-12-01)