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鼻息肉的基于人工智能的病理亚型诊断:一个多维和微观可视化研究.

Xin Luo1,2,3,4, Hansheng Li5, Jianning Chen6

  • 1Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.

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概括

一个人工智能系统 (NPSS) 通过集成显微镜 (MI) 和全幻灯片成像 (WSI) 准确诊断鼻息肉亚型并预测复发. 这种人工智能工具显著减少了诊断时间,并提高了病理学家的准确性.

关键词:
人工智能的人工智能是人工智能.显微镜图像 显微镜图像鼻的多胞体鼻的多胞体病理学的病理学整个幻灯片图像 整体幻灯片图像

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科学领域:

  • 耳鼻喉科 耳鼻喉科 耳鼻喉科
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 鼻息肉 (NP) 呈现多种不同的炎症亚型,影响临床结果.
  • 在显微镜图像 (MI) 中手动计数细胞是耗时且主观的.
  • 目前的方法限制了NP亚型和治疗决策的诊断精度.

研究的目的:

  • 开发一个基于人工智能的系统 (NPSS),用于准确的NP亚型诊断.
  • 通过使用人工智能来提高诊断效率和精度.
  • 使用集成成像数据预测NP复发.

主要方法:

  • 开发了NPSS,使用来自20家医院的2457个幻灯片,包括MI和全幻灯片成像 (WSI).
  • 在NPSS-WSI中使用PA-P2PNet进行细胞检测和U-KAN进行区域细分.
  • 利用3D重建 (3DNP) 进行空间细胞量化和后勤回归来预测复发.

主要成果:

  • 在内部和外部数据集上,NPSS实现了高性能 (F1评分为0.809,IOU为0.827).
  • NPSS显著减少了诊断时间 (例如,WSI从10,450秒到250秒),并提高了病理学家的准确性.
  • 与基于MI的模型相比,NPSS-WSI预后模型显示出更高的预测性能 (AUC 86.64%).

结论:

  • NPSS集成MI,WSI和3DNP,用于精确的NP亚型诊断和预后.
  • 人工智能系统提高了诊断效率和管理鼻多的临床实用性.
  • 在客观评估和管理鼻息肉方面,NPSS代表了重大进步.