7 papers · 1 filter
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…
GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation
Rafi Ibn Sultan, Chengyin Li, Hui Zhu +3
In geographical image segmentation, performance is often constrained by the limited availability of training data and a lack of generalizability, particularly for segmenting mobili…
BiPVL-Seg: Bidirectional Progressive Vision-Language Fusion with Global-Local Alignment for Medical Image Segmentation
Rafi Ibn Sultan, Hui Zhu, Chengyin Li +1
Medical image segmentation typically relies solely on visual data, overlooking the rich textual information clinicians use for diagnosis. Vision-language models attempt to bridge t…