医学领域基于内容的图像检索：回顾性评估、当前技术水平与未来方向。
Content-Based Image Retrieval in Medicine: Retrospective Assessment, State of the Art, and Future Directions.
作者信息
Long L Rodney, Antani Sameer, Deserno Thomas M, Thoma George R
机构信息
National Library of Medicine, USA.
出版信息
Int J Healthc Inf Syst Inform. 2009 Jan 1;4(1):1-16. doi: 10.4018/jhisi.2009010101.
Abstract
Content-based image retrieval (CBIR) technology has been proposed to benefit not only the management of increasingly large image collections, but also to aid clinical care, biomedical research, and education. Based on a literature review, we conclude that there is widespread enthusiasm for CBIR in the engineering research community, but the application of this technology to solve practical medical problems is a goal yet to be realized. Furthermore, we highlight "gaps" between desired CBIR system functionality and what has been achieved to date, present for illustration a comparative analysis of four state-of-the-art CBIR implementations using the gap approach, and suggest that high-priority gaps to be overcome lie in CBIR interfaces and functionality that better serve the clinical and biomedical research communities.
摘要
基于内容的图像检索（CBIR）技术的提出，不仅是为了便于管理日益庞大的图像集，也是为了辅助临床护理、生物医学研究和教育。基于文献综述，我们得出结论，工程研究界对CBIR普遍充满热情，但将该技术应用于解决实际医疗问题仍是一个尚未实现的目标。此外，我们强调了理想的CBIR系统功能与目前已实现功能之间的“差距”，通过差距分析方法举例展示了对四种最先进的CBIR实现方式的比较分析，并指出需要克服的高优先级差距在于能更好地服务临床和生物医学研究界的CBIR接口和功能。
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