Hassan Bagher-Ebadian, PhD

Dynamic contrast-enhanced (DCE)-MRI is widely used to assess vascular perfusion and permeability; however, conventional time-domain pharmacokinetic models often conflate flow- and leakage-driven transport. This study introduces a Laplace-domain framework to q...

Automated stereotactic radiosurgery (SRS) planning often fails to match the high conformity and complex trade-off logic of expert human dosimetrists. We hypothesized that a reasoning-based AI agent, SAGE (Secure Agent for Generative dose Expertise), could gen...

Radiotherapy planning is time-intensive, iterative, and operator dependent. AI automates planning but is not transparent, and cloud-based models threaten privacy. We developed and evaluated SAGE (Secure Agent for Generative dose Expertise), a locally hosted,...

Dynamic-contrast–enhanced (DCE) MRI enables quantitative assessment of microvascular permeability but is constrained at low field by reduced SNR and ambiguous voxel-wise model selection. This study constructs and evaluates an unsupervised probabilistic-nested...

Accurate organ-at-risk segmentation remains a critical bottleneck in MR-guided adaptive radiotherapy, consuming 20–40 minutes per fraction. Current methods treat each fraction independently, discarding patient-specific information from prior sessions. We deve...