Papers with Generating radiology
MediVLM: A Vision Language Model for Radiology Report Generation from Medical Images (2025.findings-emnlp)
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| Challenge: | Existing methods for radiology report generation from medical images are incomplete and inconsistent, fail to focus on informative regions within an image and impose strong annotation assumptions for model training. |
| Approach: | They propose a vision language model (VLM) for radiology report generation from medical images that uses a pre-trained object detector to extract the salient anatomical regions from images, an image encoder, a text encoder and a transformer based decoder to generate the final report. |
| Outcome: | The proposed model generates radiology reports even when no reports are available for training. |
CPR-RAG: Clinical Prior-Regularized Retrieval for Anatomy-Aware 3D CT Report Generation (2026.acl-long)
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| Challenge: | Existing approaches to grounding radiology reports from 3D volumetric data are limited due to visual-semantic ambiguity and lack of "normal" context. |
| Approach: | They propose a model-agnostic retrieval-augmented generation framework that integrates clinical priors into the retrieval process. |
| Outcome: | The proposed model improves clinical efficacy across state-of-the-art models. |