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eess.IV2021★ 1 cited
Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks
Yiran Wei, Yonghao Li, Xi Chen +3
Glioma is a common malignant brain tumor with distinct survival among patients. The isocitrate dehydrogenase (IDH) gene mutation provides critical diagnostic and prognostic value f…
eess.IV2021
Expectation-Maximization Regularized Deep Learning for Weakly Supervised Tumor Segmentation for Glioblastoma
Chao Li, Wenjian Huang, Xi Chen +3
We present an Expectation-Maximization (EM) Regularized Deep Learning (EMReDL) model for weakly supervised tumor segmentation. The proposed framework is tailored to glioblastoma, a…
eess.IV2020
Bayesian optimization assisted unsupervised learning for efficient intra-tumor partitioning in MRI and survival prediction for glioblastoma patients
Yifan Li, Chao Li, Stephen Price +2
Glioblastoma is profoundly heterogeneous in microstructure and vasculature, which may lead to tumor regional diversity and distinct treatment response. Although successful in tumor…