Summary of How Well Do Multi-modal Llms Interpret Ct Scans? An Auto-evaluation Framework For Analyses, by Qingqing Zhu et al.
How Well Do Multi-modal LLMs Interpret CT Scans? An Auto-Evaluation Framework for Analyses
by Qingqing Zhu, Benjamin Hou, Tejas S. Mathai, Pritam Mukherjee, Qiao Jin, Xiuying Chen, Zhizheng Wang, Ruida Cheng, Ronald M. Summers, Zhiyong Lu
First submitted to arxiv on: 8 Mar 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 This paper introduces a novel evaluation framework, GPTRadScore, for assessing the capabilities of multi-modal LLMs in generating descriptions for prospectively-identified findings on CT scans. The framework evaluates the accuracy of generated descriptions against gold-standard report sentences, analyzing their accuracy in terms of body part, location, and type of finding. The study uses a decomposition technique based on GPT-4 to compare the performance of models such as GPT-4V, Gemini Pro Vision, LLaVA-Med, and RadFM. Evaluations show a high correlation with clinician assessments and highlight the potential of GPTRadScore over traditional metrics like BLEU, METEOR, and ROUGE. A benchmark dataset annotated by clinicians will be released to contribute to future studies. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps computers better understand CT scan images, which can help radiologists do their jobs more efficiently. The problem is that there aren’t enough good datasets for training these computer models. To solve this, the researchers created a new way to evaluate how well these models do, called GPTRadScore. They tested different models, like GPT-4V and Gemini Pro Vision, and found that they can get better at describing what they see in CT scans. The study shows that computers can be trained to improve their skills even more by using the right data. |
Keywords
» Artificial intelligence » Bleu » Gemini » Gpt » Multi modal » Rouge
