University of Malaya, Kuala Lumpur, Malaysia.
J Med Syst. 2011 Aug;35(4):571-8. doi: 10.1007/s10916-009-9393-3. Epub 2009 Nov 20.
Content-based image retrieval techniques have been extensively studied for the past few years. With the growth of digital medical image databases, the demand for content-based analysis and retrieval tools has been increasing remarkably. Blood cell image is a key diagnostic tool for hematologists. An automated system that can retrieved relevant blood cell images correctly and efficiently would save the effort and time of hematologists. The purpose of this work is to develop such a content-based image retrieval system. Global color histogram and wavelet-based methods are used in the prototype. The system allows users to search by providing a query image and select one of four implemented methods. The obtained results demonstrate the proposed extended query refinement has the potential to capture a user's high level query and perception subjectivity by dynamically giving better query combinations. Color-based methods performed better than wavelet-based methods with regard to precision, recall rate and retrieval time. Shape and density of blood cells are suggested as measurements for future improvement. The system developed is useful for undergraduate education.
基于内容的图像检索技术在过去几年中得到了广泛的研究。随着数字医学图像数据库的增长，对基于内容的分析和检索工具的需求显著增加。血细胞图像是血液学家的关键诊断工具。一个能够正确、高效地检索相关血细胞图像的自动化系统将为血液学家节省精力和时间。本工作的目的是开发这样一个基于内容的图像检索系统。原型中使用了全局颜色直方图和基于小波的方法。系统允许用户通过提供查询图像进行搜索，并选择四种实现方法之一。所得结果表明，所提出的扩展查询细化具有通过动态提供更好的查询组合来捕获用户高级查询和感知主观性的潜力。在精度、召回率和检索时间方面，基于颜色的方法比基于小波的方法表现更好。建议将血细胞的形状和密度作为未来改进的测量方法。开发的系统对本科教育很有用。
