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5 papers
Automating RT Planning at Scale: High Quality Data For AI Training
Riqiang Gao, Mamadou Diallo, Han Liu +10
Radiotherapy (RT) planning is complex, subjective, and time-intensive. Advances with artificial intelligence (AI) promise to improve its precision and efficiency, but progress is o…
Any2Any 3D Diffusion Models with Knowledge Transfer: A Radiotherapy Planning Study
Yuhan Wang, Zihan Li, Han Liu +7
Voxel-wise dose prediction is a critical yet challenging task in practical radiotherapy (RT) planning, as bespoke models trained from scratch often struggle to generalize across di…
Enhancing Fine-Grained Spatial Grounding in 3D CT Report Generation via Discriminative Guidance
Chenyu Wang, Weicheng Dai, Han Liu +2
Vision--language models (VLMs) for radiology report generation (RRG) can produce long-form chest CT reports from volumetric scans and show strong potential to improve radiology wor…
PanDx: AI-assisted Early Detection of Pancreatic Ductal Adenocarcinoma on Contrast-enhanced CT
Han Liu, Riqiang Gao, Eileen Krieg +1
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive forms of pancreatic cancer and is often diagnosed at an advanced stage due to subtle early imaging signs. To e…
Demo: Generative AI helps Radiotherapy Planning with User Preference
Riqiang Gao, Simon Arberet, Martin Kraus +5
Radiotherapy planning is a highly complex process that often varies significantly across institutions and individual planners. Most existing deep learning approaches for 3D dose pr…