创建一个正常组织的地图,用于通过异常检测修补WSI修剪WSI修补
Peyman Nejat1, Areej Alsaafin1, Ghazal Alabtah1
1KIMIA Lab, Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.
Scientific reports
|February 17, 2024
概括
从整个幻灯片图像 (WSI) 创建正常组织图谱,通过去除正常组织来帮助计算病理学. 这提高了癌症检测和分析中对异常区域的关注度.
科学领域:
- 计算病理学计算病理学
- 数字病理学数字病理学
- 组织病理学图像分析分析.
背景情况:
- 整个幻灯片图像 (WSIs) 分析通常包括正常组织学,这可能是多余的.
- 现有的计算病理学方法忽视了正常组织对分析的影响.
- 有效地识别和排除正常组织对于准确检测病理病变至关重要.
研究的目的:
- 提出并验证一种创建"正常组织图谱"的新方法,只使用正常的活检WSIs.
- 通过消除正常组织碎片,展示本地图集如何提高选定的WSI补丁的代表性.
- 提高搜索引擎和计算病理学分析工具的性能.
主要方法:
- 使用107个正常皮肤WSIs构建一个正常组织地图.
- 应用阿特拉斯来过皮肤状细胞癌 (553 WSIs) 和乳腺癌 (451 WSIs) WSIs中的补丁.
- 评估对补丁选择和搜索性能的影响,使用离开一个患者的验证.
主要成果:
- 通常的地图集将WSI选定的补丁数量减少了30%至50%.
- 在使用正常的地图集之后,索引和搜索性能保持不变.
- 在皮肤和乳腺癌数据集上的验证证实了该方法的有效性.
结论:
- 拟议的正常组织地图是对代表性异常WSI补丁的无监督选择的有希望的方法.
- 这种方法通过专注于诊断相关的组织,提高了计算病理学的效率和准确性.
- 该地图书通过减少数据量,同时保留必要的病理信息,促进了改进的分析.
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