H. Akbari

Latest

• Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome
• Accurate And Generalizable Pre-operative Prognostic Stratification Of Glioblastoma Patients Using Integrative Quantitative Radiomic Analysis Of Conventional MRI
• Radiomic Features from Multi-Institutional Glioblastoma MRI Offer Additive Prognostic Value to Clinical and Genomic Markers: Focus on TCGA-GBM Collection
• Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features
• Segmentation of Gliomas in Pre-operative and Post-operative Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework
• GLISTRboost: combining multimodal MRI segmentation, registration, and biophysical tumor growth modeling with gradient boosting machines for glioma segmentation