CVPR

Beyond Fluency: A Clinical Benchmark and Anomaly-Enhanced Baseline for Spine MRI Report Generation

超越流畅性：脊柱MRI报告生成的临床基准与异常增强基线

Bruno Palau, Franziska Vogt, Daria Laslo, Haobo Li, Ender Konukoglu, Maria Monzon, Catherine R. Jutzeler

机构 * ETH Zurich（苏黎世联邦理工学院） ； Swiss Institute of Bioinformatics (SIB)（瑞士生物信息学研究所） 纠错

AI总结 该研究针对放射学报告的耗时与阅片差异问题，构建腰椎MRI的VLM临床基准，提出半监督U-Net++生成异常热图增强VLM的框架，提升诊断可靠性与可解释性。

Comments Maria Monzon and Catherine R. Jutzeler contributed equally as shared last authors. Accepted at the CV4Clinic Workshop, CVPR 2026

Journal ref Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2026, pp. 6759-6770