Summary of Aligning Knowledge Concepts to Whole Slide Images For Precise Histopathology Image Analysis, by Weiqin Zhao et al.
Aligning Knowledge Concepts to Whole Slide Images for Precise Histopathology Image Analysis
by Weiqin Zhao, Ziyu Guo, Yinshuang Fan, Yuming Jiang, Maximus Yeung, Lequan Yu
First submitted to arxiv on: 27 Nov 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
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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 knowledge concept-based Multiple Instance Learning (MIL) framework called ConcepPath is proposed to fill a gap in Whole Slide Images (WSIs) analysis. The framework utilizes GPT-4 to induce reliable disease-specific human expert concepts from medical literature, which are then combined with purely learnable concepts to extract complementary knowledge from training data. The WSIs are aligned to these linguistic knowledge concepts using a pathology vision-language model as the basic building component. ConcepPath is applied to lung cancer subtyping, breast cancer HER2 scoring, and gastric cancer immunotherapy-sensitive subtyping tasks, significantly outperforming previous state-of-the-art (SOTA) methods that lack human expert knowledge guidance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ConcepPath is a new way to analyze big images of body tissues. Usually, these images are too big and not detailed enough for computers to understand. This makes it hard for machines to learn about different diseases from these images. To solve this problem, ConcepPath uses special language models to teach the computer how humans think about certain diseases. The computer then uses this knowledge to look at the images and make decisions. ConcepPath is better than other methods because it includes human ideas when making decisions. |
Keywords
» Artificial intelligence » Gpt » Language model
