Summary of Padchest-gr: a Bilingual Chest X-ray Dataset For Grounded Radiology Report Generation, by Daniel C. Castro et al.
PadChest-GR: A Bilingual Chest X-ray Dataset for Grounded Radiology Report Generation
by Daniel C. Castro, Aurelia Bustos, Shruthi Bannur, Stephanie L. Hyland, Kenza Bouzid, Maria Teodora Wetscherek, Maria Dolores Sánchez-Valverde, Lara Jaques-Pérez, Lourdes Pérez-Rodríguez, Kenji Takeda, José María Salinas, Javier Alvarez-Valle, Joaquín Galant Herrero, Antonio Pertusa
First submitted to arxiv on: 7 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel dataset called PadChest-GR is introduced, designed to train grounded radiology report generation (GRRG) models for chest X-ray (CXR) images. The dataset comprises 4,555 CXR studies with grounded reports in both English and Spanish, featuring complete lists of sentences describing individual findings on the image. The report includes categorical labels for finding type, locations, and progression, as well as bounding box annotations from multiple readers. PadChest-GR is the first manually curated dataset for training GRRG models, offering a valuable resource for developing and evaluating these models in understanding and interpreting radiological images. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trying to teach computers to write medical reports about X-rays. To do this, we need special datasets that help train the computers. This paper creates one of those datasets, called PadChest-GR, which has lots of X-ray pictures and descriptions of what’s found in each picture. The dataset is important because it helps computers learn to write clear and accurate reports about what they see on X-rays. |
Keywords
» Artificial intelligence » Bounding box
