1 citations · 1 across the 2 of their papers we have counts for
5 papers
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…
Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma
Yifan Li, Chao Li, Yiran Wei +3
Glioblastoma is profoundly heterogeneous in regional microstructure and vasculature. Characterizing the spatial heterogeneity of glioblastoma could lead to more precise treatment.…
BrainNetGAN: Data augmentation of brain connectivity using generative adversarial network for dementia classification
Chao Li, Yiran Wei, Xi Chen +1
Alzheimer's disease (AD) is the most common age-related dementia. It remains a challenge to identify the individuals at risk of dementia for precise management. Brain MRI offers a…
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…
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…