VIM-Polyp: Multimodal Colon Polyp Dataset with Video, Histopathology, and Protein Expression
8.0
来源：
Nature
关键字：
computational pathology
发布时间：
2025-12-04 03:40
摘要：
The VIM-Polyp dataset is a groundbreaking resource that combines colonoscopy videos, histopathology images, and immunohistochemical data from 201 patients with colon polyps. This multimodal dataset aims to enhance the accuracy of polyp detection and characterization, which is crucial for colorectal cancer diagnosis and treatment. By providing a comprehensive collection of data, it facilitates research and clinical applications, ultimately improving patient outcomes. The dataset's open accessibility encourages further exploration and innovation in the field of colorectal cancer.
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domain_focus
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business_impact
1.0
scientific_rigor
1.5
timeliness_innovation
1.5
investment_perspective
2.5
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1.0
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关键证据
The dataset includes 202 colonoscopy videos and 1903 histopathology images, providing critical insights into colon polyp diagnosis.
It supports benchmarking and transfer learning studies, addressing the lack of multimodal datasets in colorectal cancer research.
The study emphasizes the importance of accurate polyp detection and characterization for improving patient outcomes.
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AI评分总结
The VIM-Polyp dataset is a groundbreaking resource that combines colonoscopy videos, histopathology images, and immunohistochemical data from 201 patients with colon polyps. This multimodal dataset aims to enhance the accuracy of polyp detection and characterization, which is crucial for colorectal cancer diagnosis and treatment. By providing a comprehensive collection of data, it facilitates research and clinical applications, ultimately improving patient outcomes. The dataset's open accessibility encourages further exploration and innovation in the field of colorectal cancer.