Computer Science > Computation and Language
arXiv:2406.04449 (cs)
[Submitted on 6 Jun 2024 (v1), last revised 20 Sep 2024 (this version, v2)]
Title:MAIRA-2: Grounded Radiology Report Generation
Authors:Shruthi Bannur,Kenza Bouzid,Daniel C. Castro,Anton Schwaighofer,Anja Thieme,Sam Bond-Taylor,Maximilian Ilse,Fernando Pérez-García,Valentina Salvatelli,Harshita Sharma,Felix Meissen,Mercy Ranjit,Shaury Srivastav,Julia Gong,Noel C. F. Codella,Fabian Falck,Ozan Oktay,Matthew P. Lungren,Maria Teodora Wetscherek,Javier Alvarez-Valle,Stephanie L. Hyland
View a PDF of the paper titled MAIRA-2: Grounded Radiology Report Generation, by Shruthi Bannur and 20 other authors
View PDFAbstract:Radiology reporting is a complex task requiring detailed medical image understanding and precise language generation, for which generative multimodal models offer a promising solution. However, to impact clinical practice, models must achieve a high level of both verifiable performance and utility. We augment the utility of automated report generation by incorporating localisation of individual findings on the image - a task we call grounded report generation - and enhance performance by incorporating realistic reporting context as inputs. We design a novel evaluation framework (RadFact) leveraging the logical inference capabilities of large language models (LLMs) to quantify report correctness and completeness at the level of individual sentences, while supporting the new task of grounded reporting. We develop MAIRA-2, a large radiology-specific multimodal model designed to generate chest X-ray reports with and without grounding. MAIRA-2 achieves state of the art on existing report generation benchmarks and establishes the novel task of grounded report generation.
| Comments: | 72 pages, 21 figures. v2 updates the model and adds results on the PadChest-GR dataset |
| Subjects: | Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2406.04449 [cs.CL] |
| (orarXiv:2406.04449v2 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2406.04449 arXiv-issued DOI via DataCite |
Submission history
From: Shruthi Bannur [view email][v1] Thu, 6 Jun 2024 19:12:41 UTC (3,478 KB)
[v2] Fri, 20 Sep 2024 17:17:43 UTC (9,150 KB)
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View a PDF of the paper titled MAIRA-2: Grounded Radiology Report Generation, by Shruthi Bannur and 20 other authors
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