GateSPINE: Gated Cross-View Fusion for Lumbar Spine MRI Report Generation
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GateSPINE is a vision‑language framework designed for automated lumbar spine MRI report generation. It fuses sagittal T1 and T2 volumes using a training‑free gated cross‑view fusion module, then encodes the fused sagittal and axial volumes with parallel 3D encoders before decoding the combined representation into a report. Evaluated on three datasets, GateSPINE achieves the highest clinical efficacy F1 scores, improving recall across all datasets while remaining competitive on standard natural language generation metrics.
arXiv:2607. 19696v1 Announce Type: cross Abstract: The accurate diagnosis of spinal pathologies depends heavily on radiological interpretation, yet automated systems are hindered by the lack of diverse, high-quality benchmarks.
The accurate diagnosis of spinal pathologies depends heavily on radiological interpretation, yet automated systems are hindered by the lack of diverse, high-quality benchmarks. In this study, we present PhenSPINE, a Magnetic Resonance Imaging dataset comprising 16,813 images from 250 patients, curated to facilitate advanced deep learning research.
arXiv:2606. 31099v1 Announce Type: cross Abstract: Recent years have seen substantial advances in radiology report generation (RRG), yet existing approaches predominantly adopt direct feature fusion when handling multi-view X-ray images.
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arXiv:2605.30984v2 Announce Type: replace-cross Abstract: Modern 3D medical vision-language models (VLMs) can generate fluent radiology-style text while exhibit critically low pathology detection and...