Differentiating IDH status in human gliomas using machine learning and multiparametric MR/PET

Differentiating IDH status in human gliomas using machine learning and multiparametric MR/PET

Abstract Background The purpose of this study was to develop a voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) positron emission tomography (PET) images using an unsupervised, two-level clustering approach foll...

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Bibliographic Details
Main Authors: Hiroyuki Tatekawa, Akifumi Hagiwara, Hiroyuki Uetani, Shadfar Bahri, Catalina Raymond, Albert Lai, Timothy F. Cloughesy, Phioanh L. Nghiemphu, Linda M. Liau, Whitney B. Pope, Noriko Salamon, Benjamin M. Ellingson
Format: Article
Language:English
Published: BMC 2021-03-01
Series:Cancer Imaging
Subjects:
Machine learning
18F-DOPA PET
MRI
IDH mutation
Clustering
Diffuse glioma
Online Access:https://doi.org/10.1186/s40644-021-00396-5

Internet

https://doi.org/10.1186/s40644-021-00396-5

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