Optimizing Texture Retrieving Model for Multimodal MR Image-Based Support Vector Machine for Classifying Glioma-Reference-Cited by-同舟云学术

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Optimizing Texture Retrieving Model for Multimodal MR Image-Based Support Vector Machine for Classifying Glioma

Published:2019-01-09 Issue:5 Volume:49 Page:1263-1274
ISSN:1053-1807
Container-title:Journal of Magnetic Resonance Imaging
language:en
Short-container-title:J. Magn. Reson. Imaging

Author:

Yang Yang¹,Yan Lin-Feng¹,Zhang Xin¹,Nan Hai-Yan¹,Hu Yu-Chuan¹,Han Yu¹,Zhang Jin¹,Liu Zhi-Cheng¹,Sun Ying-Zhi¹,Tian Qiang¹,Yu Ying¹,Sun Qian¹,Wang Si-Yuan²,Zhang Xiao²,Wang Wen¹,Cui Guang-Bin¹

Affiliation:

1. Functional and Molecular Imaging Key Lab of Shaanxi Province, Department of Radiology, Tangdu Hospital; Air Force Medical University (Fourth Military Medical University); Xi'an Shaanxi China

2. Student Brigade; Air Force Medical University (Fourth Military Medical University); Xi'an Shaanxi China

Funder

GE Healthcare

NordicNeuroLab in Norway

National Key Research and Development Program of China

National Natural Science Foundation of China

Innovation Foundation of Tangdu Hospital

Young Seeding Talent Foundation of Tangdu Hospital

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/jmri.26524/fullpdf

Reference40 articles.

1. Epidemiology and molecular pathology of glioma;Schwartzbaum;Nat Clin Pract Neurol,2006

2. 2016 World Health Organization Classification of central nervous system tumors: an era of molecular biology;Hoshide;World Neurosurg,2016

3. Comparison of cerebral blood volume and permeability in preoperative grading of intracranial glioma using CT perfusion imaging;Ding;Neuroradiology,2006

4. Brain MRI: tumor evaluation;Young;J Magn Reson Imaging,2006

5. ADC texture-an imaging biomarker for high-grade glioma?;Brynolfsson;Med Phys,2014

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