对上下文区域的像素级注释,以可靠地诊断来自组织病理性WSI的乳腺淋巴结转移
Richa Malviya Dutta1, Arif Ahmed Sekh2, Prarthana Raghuram3
1Rajendra Mishra School of Engineering Entrepreneurship, Indian Institute of Technology Kharagpur, 721302 West Bengal, India.
Data in brief
|January 21, 2026
概括
这项研究呈现了一种新型数据集,即精心注释的乳腺淋巴结转移全片图像 (WSI). 这些经过专家验证的像素级注释通过提供具有诊断意义的区域和背景来增强自动化癌症诊断.
科学领域:
- 数字病理学数字病理学
- 医学图像分析 医学图像分析
- 计算瘤学计算瘤学
背景情况:
- 在数字病理学中,监督自动诊断严重依赖于注释图像.
- 显著缺乏高质量的,专家注释的数据集,阻碍了可靠的癌症诊断工具的开发.
研究的目的:
- 创建一个有价值的乳腺淋巴结转移整体幻灯片图像 (WSI) 的数据集,精确的,像素级的注释.
- 为改善诊断准确性,提供超出仅仅转移性区域的重要注释.
主要方法:
- 采用了两阶段,高值的像素级注释协议.
- 来自Camelyon16数据集的73张训练图像被医生注释并由病理学家核实.
- 标注包括诊断显著的组织,背景组织和文物.
主要成果:
- 为乳腺淋巴结转移 WSI 创建了一个独特的数据集,包含经过专家验证的像素级注释.
- 该数据集将区域分类为具有诊断意义的组织,背景和文物.
- 注释为癌症诊断提供了关键的上下文信息.
结论:
- 这一数据集促进了可靠的补丁准备,用于训练自动诊断系统.
- 它支持从WSI提取显著区域用于转移诊断.
- 值得信赖的注释可以加速将研究成果转化为临床实践.
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