TY - JOUR AU - Tatekawa, Hiroyuki AU - Hagiwara, Akifumi AU - Uetani, Hiroyuki AU - Bahri, Shadfar AU - Raymond, Catalina AU - Lai, Albert AU - Cloughesy, Timothy F. AU - Nghiemphu, Phioanh L. AU - Liau, Linda M. AU - Pope, Whitney B. AU - Salamon, Noriko AU - Ellingson, Benjamin M. PY - 2021 DA - 2021/03/10 TI - Differentiating IDH status in human gliomas using machine learning and multiparametric MR/PET JO - Cancer Imaging SP - 27 VL - 21 IS - 1 AB - 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 followed by support vector machine in order to classify the isocitrate dehydrogenase (IDH) status of gliomas. SN - 1470-7330 UR - https://doi.org/10.1186/s40644-021-00396-5 DO - 10.1186/s40644-021-00396-5 ID - Tatekawa2021 ER -