Author profile
Department of Radiation Oncology, Stanford University
Deep learning-based image reconstruction has shown substantial promise for addressing the highly non-uniform and under-sampled projections encountered in nonstop gated CBCT (ngCBCT). However, due to the statistical nature of data-driven learning and inherent...
An improved imager and software (HyperSight on a Varian TrueBeam linac) feature a larger detector panel and increase the maximum gantry rotation speed for CBCT imaging to 1.5 revolutions per minute (rpm). While enabling faster acquisition, its impact on free-...
In non-coplanar SBRT/SRS, efficient high-resolution volumetric imaging under limited-angle non-coplanar CBCT (LA-NC-CBCT) acquisition is critical for avoiding potential collisions while ensuring treatment delivery accuracy. However, severe data occlusion outs...
In respiratory gating radiotherapy (RG-RT), pretreatment imaging—particularly gated cone-beam CT (gCBCT)—is essential but operationally inefficient. Current gCBCT on C-arm linear accelerator is time-consuming (2–8 minutes) and often requires re-scans when gat...
Nonstop gated CBCT (ngCBCT) was developed to overcome the limitations of current gated CBCT (gCBCT), enabling 2-8x faster acquisitions and 2.5-3.5x lower imaging dose. However, ngCBCT produces highly non-uniform and under-sampled projection data that challeng...