在癌症成像档案中对非图像数据的本体学增强表示
Jonathan P Bona1, Tracy S Nolan1, Mathias Brochhausen1
1Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States.
概括
癌症成像档案 (TCIA) 现在集成了使用开放生物医学本体学的各种非图像癌症研究数据. 这提高了研究癌症的研究人员的可访问性和可用性.
科学领域:
- 生物医学信息学 生物医学信息学
- 放射学 放射学是一门学科.
- 癌症研究 癌症研究
背景情况:
- 癌症成像档案 (TCIA) 为研究提供了超过1100万张未识别的癌症相关医学图像.
- 根据疾病,模式或研究重点,TCIA将数据组织成DICOM格式的放射学集合.
- 许多TCIA收藏包含多样化的非图像数据集,缺乏标准化表示,阻碍了可访问性.
研究的目的:
- 提高TCIA内部各种非图像数据集的可访问性和可用性.
- 将非图像数据转化为集成的语义表示,使用开放的生物医学本体 (OBOs).
- 为了记录挑战,并展示精选的TCIA数据集的详细语义表示.
主要方法:
- 应用开放的生物医学本体学,以语义地表示多样化的非图像数据.
- 开发了一种共同的方法来整合和标准化各种数据格式.
- 分析和记录了在精选的TCIA收藏中遇到的数据表示挑战.
主要成果:
- 成功地将异质的非图像数据集转化为集成的语义表示.
- 证明了使用OBOs用于标准化各种癌症研究数据的可行性.
- 确定并详细说明在TCIA中表示非图像数据的具体障碍.
结论:
- 使用OBOs的语义集成显著提高了TCIA中非图像数据的可访问性和可用性.
- 标准化表示方便更强大的数据分析和研究重复使用.
- 解决数据表示挑战对于最大限度地提高综合研究档案的价值至关重要.
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