用于约翰病的检测和研究的基因病理图像数据集
Wael Hananeh1, Mohammad Fraiwan2
1Department of Veterinary Pathology and Public Health, Faculty of Veterinary Medicine, Jordan University of Science and Technology, P.O. Box 3030 Irbid 22110 Jordan.
Data in brief
|September 2, 2025
概括
这项研究介绍了约翰的第一个公共数据集.
科学领域:
- 兽医病理学
- 数字病理学
- 在动物健康领域的机器学习
背景情况:
- 约翰氏病 (肺结核病) 是一种由Mycobacterium avium亚种肺结核病 (MAP) 引起的慢性肠道感染.
- 准确的诊断对于控制至关重要,但传统的组织病理学有局限性,包括专家依赖性和观察者之间的变异性.
- 开发自动诊断工具需要高质量的注释图像数据.
研究的目的:
- 为了呈现一种新的,精心策划的, 针对约翰病的基因病学图像.
- 促进计算机辅助诊断和机器学习模型的开发,以检测约翰氏病.
- 为兽医病理学培训提供教育资源.
主要方法:
- 从反动物中采集组织样本,证实对约翰氏病的阳性或阴性.
- 标准的血素和素 (H&E) 染色和高分辨率的数字幻灯片扫描.
- 每个图像的注释用诊断标签经过认证病理学家的验证.
主要成果:
- 一个公开可用的基因病理图像对约翰的疾病现在可用.
- 数据集按疾病状况 (阳性/阴性) 进行整理,使得监督机器学习成为可能.
- 这项资源支持数字病理学和自动诊断系统的研究.
结论:
- 这一数据集是第一个致力于约翰氏病组织病理的数据集.
- 这项资源将加速自动化约翰病检测和兽医教育的研究.
- 预计这一数据集的可用性将提高反动物的诊断准确性和疾病管理.
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