Astra generates style-consistent multi-organ CT reports that generalize across institutions via report harmonization plus GRPO reinforcement learning, improving clinical drafting and enabling synthetic pretraining.
arXiv preprint arXiv:2409.19330 , year=
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2026 3representative citing papers
TIF-GRPO uses integral feedback on pseudo-temporal trajectories to regulate anatomy-aware rewards in RL for clinical faithfulness in volumetric CT analysis.
UniReason-Med introduces a unified framework for 2D and 3D medical VQA with shared grounded reasoning, trained on a 220K dataset, claiming that joint 2D+3D supervision improves 3D performance over 3D-only training.
citing papers explorer
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Astra: a generalizable report generation foundation model for 3D computed tomography
Astra generates style-consistent multi-organ CT reports that generalize across institutions via report harmonization plus GRPO reinforcement learning, improving clinical drafting and enabling synthetic pretraining.
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Regulating Anatomy-Aware Rewards via Trajectory-Integral Feedback for Volumetric Computed Tomography Analysis
TIF-GRPO uses integral feedback on pseudo-temporal trajectories to regulate anatomy-aware rewards in RL for clinical faithfulness in volumetric CT analysis.
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UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA
UniReason-Med introduces a unified framework for 2D and 3D medical VQA with shared grounded reasoning, trained on a 220K dataset, claiming that joint 2D+3D supervision improves 3D performance over 3D-only training.