10 papers
A Bounded Reclaim Actuator for PSI-Guided Compressed Memory: A Controlled Ablation
Abhiyan Dhakal, Sanjog Sigdel
When the aggregate working set of active processes exceeds physical RAM capacity, the machine experiences memory pressure. Applications may therefore slow down before the kernel ki…
A Neighborhood Attention Transformer Network for Enhanced 3D Segmentation of the Left Anterior Descending Artery
Rafi Ibn Sultan, Chengyin Li, Yiannos Demetriou +6
Background: Accurate segmentation of the Left Anterior Descending (LAD) artery in 3D free-breathing, non-contrast CT is critical for cardiac dose sparing in thoracic radiotherapy.…
Robustness of Transformer-Based Fluence Map Prediction Under Clinically Realistic Perturbations
Ujunwa Mgboh, Rafi Ibn Sultan, Joshua Kim +2
Learning-based fluence map prediction offers a fast alternative to iterative inverse planning in intensity-modulated radiation therapy (IMRT), but its robustness under realistic di…
WalkGPT: Grounded Vision-Language Conversation with Depth-Aware Segmentation for Pedestrian Navigation
Rafi Ibn Sultan, Hui Zhu, Xiangyu Zhou +4
Ensuring accessible pedestrian navigation requires reasoning about both semantic and spatial aspects of complex urban scenes, a challenge that existing Large Vision-Language Models…
FluenceFormer: Transformer-Driven Multi-Beam Fluence Map Regression for Radiotherapy Planning
Ujunwa Mgboh, Rafi Ibn Sultan, Joshua Kim +2
Fluence map prediction is central to automated radiotherapy planning but remains an ill-posed inverse problem due to the complex relationship between volumetric anatomy and beam-in…
Fluence Map Prediction with Deep Learning: A Transformer-based Approach
Ujunwa Mgboh, Rafi Sultan, Dongxiao Zhu +1
Accurate fluence map prediction is essential in intensity-modulated radiation therapy (IMRT) to maximize tumor coverage while minimizing dose to healthy tissues. Conventional optim…