Summary of Slidechat: a Large Vision-language Assistant For Whole-slide Pathology Image Understanding, by Ying Chen et al.
SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understanding
by Ying Chen, Guoan Wang, Yuanfeng Ji, Yanjun Li, Jin Ye, Tianbin Li, Ming Hu, Rongshan Yu, Yu Qiao, Junjun He
First submitted to arxiv on: 15 Oct 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 The paper introduces SlideChat, a vision-language assistant that can understand and respond to instructions related to whole-slide images in computational pathology. The model is designed to handle gigapixel-sized images and can engage in multimodal conversations to provide complex responses across various pathology scenarios. To support the development of SlideChat, the authors created the largest instruction-following dataset for whole-slide images, called SlideInstruction. They also proposed a new benchmark, SlideBench, which combines captioning and visual question-answering tasks to evaluate the model’s capabilities in different clinical settings. The results show that SlideChat outperforms both general and specialized multimodal large language models on 18 out of 22 tasks, achieving state-of-the-art performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary SlideChat is a new tool that helps computers understand huge images of medical samples. These images are hard to analyze because they’re so big. The computer program can talk back to you in different ways and answer questions about the images. To make this program work, scientists created a special set of instructions and tested it on many different kinds of images. They found that their tool is better than others at understanding these types of images. |
Keywords
» Artificial intelligence » Question answering
