开发一个正常腹部和骨盆计算机断层扫描 (RADAPT) 的放射学图谱数据集
Elisavet Kapetanou1,2, Stylianos Malamas3, Dimitrios Leventis4,2
1Biomedical Engineering Graduate Programme, School of Medicine, University of Crete, Heraklion, Greece.
Journal of imaging informatics in medicine
|February 21, 2024
概括
这项研究创建了第一个公共放射学数据集,对年轻成年人的正常腹部和盆腔解剖学. 这种宝贵的资源支持开发和验证用于医学成像分析的AI模型.
科学领域:
- 医疗成像医学成像
- 无线电学 (Radiomics) 是一种辐射学.
- 计算生物学 计算生物学
背景情况:
- 现有的地图集涵盖了基因组学,转录组学,蛋白质组学和代谢组学.
- 目前还缺少一个全面的放射学地图,用于正常解剖学.
- 放射学数据对于理解生物表型和疾病至关重要.
研究的目的:
- 系统地创建一个放射学数据集的正常腹部和盆腔解剖学.
- 建立一个开发和验证基于放射学计算模型的基础.
- 为研究界提供公开可访问的资源.
主要方法:
- 对531名健康年轻成年人 (17-36岁) 的CT扫描进行了回顾性分析.
- 排除有异常发现的解剖结构.
- 使用深度学习 (TotalSegmentator in 3DSlicer) 对53个解剖结构进行自动细分.
- 使用PyRadiomics提取放射学特征 (第一顺序,纹理,波束,LoG).
主要成果:
- 从531名患者 (250名女性,281名男性) 中生成了一个放射学数据集.
- 从526个非对比和400个对比增强的CT系列中提取了特征.
- 该数据集包括多达53个细分解剖结构的放射学特征.
- 建立了一个Github存储库,以便公开访问数据.
结论:
- 这项研究成功地建立了一个新的,公开可用的放射学数据集,用于正常的腹部和骨盆解剖.
- 这一数据集是推动放射学研究和AI模型开发的关键资源.
- 促进医疗成像中的标准化模型开发和验证.
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