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多中心像素级撕裂半径细分数据集与多模式成像用于干眼诊断.

Xiaoyu Chen1, Kesheng Wang2, Kunhui Xu1

  • 1National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China.

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这项研究引入了一种新的多式联络数据集,用于下眼半径细分,这对于诊断干眼疾病至关重要. 这种AI准备的数据集将推进自动化眼分泌分析和干眼研究.

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科学领域:

  • 眼科医生 眼科 眼科
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 干眼疾病涉及眼异常,影响质量,数量和流体动力学.
  • 下面的眼半月体高度 (TMH) 是眼分泌和稳定性的关键指标,通常是手动测量.
  • 精确的TMH评估对于干眼诊断至关重要,但手动测量是耗时的.

研究的目的:

  • 引入一个多中心,多式联运,像素级数据集,用于下面的眼半月细分.
  • 促进人工智能 (AI) 模型的开发和验证,用于自动化TMH分析.
  • 支持创建标准化医疗图像数据库,用于干眼研究.

主要方法:

  • 从中国的五个中心收集了1693张彩色和1739张红外图像.
  • 开发了一种人机交互式方法,用于生成像素级分段标签.
  • 创建了一个包含图像和相应细分面具的多式联运数据集.

主要成果:

  • 引入了第一个公开可用的多式联络流阴道细分数据集.
  • 数据集包括各种成像模式 (彩色和红外) 和详细的细分标签.
  • 该数据集包括1693张彩色和1739张红外图像,专家生成了标签.

结论:

  • 开发的数据集对于训练人工智能模型进行自动化TMH细分至关重要.
  • 预计这笔资金将促进干眼诊断和治疗方面的研究.
  • 该数据集将有助于建立用于眼科研究的标准化医学图像数据库.