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صفحه اصلی
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سی امین کنفرانس بین المللی مهندسی برق
Combination of Classifiers to Detecting Grade of Gliblastoma using MRS
نویسندگان :
Roqaie Moqadam
1
Nazila Loghmani
2
Meysam Siyahmansoori
3
Armin Allahverdy
4
1- دانشگاه علوم پزشکی تهران
2- Northeastern University
3- دانشگاه علوم پزشکی کرمانشاه
4- دانشگاه علوم پزشکی مازندران
کلمات کلیدی :
Magnetic Resonance Spectroscopy, Glioma, Classifier
چکیده :
Glioma is classified into Low Grade Glioma and High Grade Glioma. Because of difference in patients’ survival, it is important to classify patients into each grade. In this study, 214 glioma patients were classified into these two grades using Choline and N-acetylaspartate as extracted metabolites from Magnetic Resonance Spectroscopy and combination of Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and Artificial Neuro-Fuzzy Inference System (ANFIS) as classifiers. Results showed that using ANFIS had the best accuracy between classifiers and combination of MLP and ANFIS had the best accuracy between different combinations of classifiers. Moreover, results showed that, concentration of Choline and N-acetylaspartate are suitable features to discriminating low and high grade glioma.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 43.6.0
