Summary of Improving Factuality Of 3d Brain Mri Report Generation with Paired Image-domain Retrieval and Text-domain Augmentation, by Junhyeok Lee et al.
Improving Factuality of 3D Brain MRI Report Generation with Paired Image-domain Retrieval and Text-domain Augmentation
by Junhyeok Lee, Yujin Oh, Dahyoun Lee, Hyon Keun Joh, Chul-Ho Sohn, Sung Hyun Baik, Cheol Kyu Jung, Jung Hyun Park, Kyu Sung Choi, Byung-Hoon Kim, Jong Chul Ye
First submitted to arxiv on: 23 Nov 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG); Image and Video Processing (eess.IV)
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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 new framework, called Paired Image-Domain Retrieval and Text-Domain Augmentation (PIRTA), is proposed for generating accurate clinician-interpretative AIS radiology reports from diffusion-weighted imaging (DWI) scans. The approach mitigates the difficulty of cross-modal mapping by retrieving similar DWI images with paired ground-truth text reports, which are then used to augment the report generation process. Experimental results on extensive in-house and public datasets show that PIRTA can accurately retrieve relevant reports from 3D DWI images, outperforming direct image-to-text generation using state-of-the-art multimodal language models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way to help doctors write accurate medical reports is being developed. The method uses a special technique called Paired Image-Domain Retrieval and Text-Domain Augmentation (PIRTA). PIRTA helps computers understand the connection between pictures of the brain and written notes from doctors. This makes it possible to generate accurate medical reports that are helpful for doctors. The new approach is tested on many images and written reports, and it does a better job than other methods. |
Keywords
» Artificial intelligence » Diffusion » Text generation
