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<p>Colonoscopy is currently one of the most sensitive screening methods for colorectal cancer. This study investigates the frontiers of intelligent colonoscopy techniques and their prospective implications for multimodal medical applications. With this goal, we begin by assessing the current data-centric and model-centric landscapes through four tasks for colonoscopic scene perception, including classification, detection, segmentation, and vision-language understanding. Our assessment reveals domain-specific challenges and underscores the need for further multimodal research in colonoscopy. To address these gaps, we establish three foundational initiatives: a large-scale multimodal instruction tuning dataset ColonINST, a colonoscopy-designed multimodal language model ColonGPT, and a multimodal benchmark. To facilitate continuous advancements in this rapidly evolving field, we provide a public website for the latest updates: <a href="https://github.com/ai4colonoscopy/IntelliScope">https://github.com/ai4colonoscopy/IntelliScope</a>.</p>

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Frontiers in Intelligent Colonoscopy

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月7日

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  • Ge-Peng Ji,
  • Jingyi Liu,
  • Peng Xu,
  • Nick Barnes,
  • Fahad Shahbaz Khan,
  • Salman Khan,
  • Deng-Ping Fan

摘要

Colonoscopy is currently one of the most sensitive screening methods for colorectal cancer. This study investigates the frontiers of intelligent colonoscopy techniques and their prospective implications for multimodal medical applications. With this goal, we begin by assessing the current data-centric and model-centric landscapes through four tasks for colonoscopic scene perception, including classification, detection, segmentation, and vision-language understanding. Our assessment reveals domain-specific challenges and underscores the need for further multimodal research in colonoscopy. To address these gaps, we establish three foundational initiatives: a large-scale multimodal instruction tuning dataset ColonINST, a colonoscopy-designed multimodal language model ColonGPT, and a multimodal benchmark. To facilitate continuous advancements in this rapidly evolving field, we provide a public website for the latest updates: https://github.com/ai4colonoscopy/IntelliScope.