A Collaborative Biomedical Image-Mining Framework: Application on the Image Analysis of Microscopic Kidney Biopsies
A Collaborative Biomedical Image-Mining Framework: Application on the Image Analysis of Microscopic Kidney Biopsies
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DOI：
10.1109/titb.2012.2224666
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发表时间：
2013-01-01
影响因子：
7.7
通讯作者：
Maglogiannis, Ilias
中科院分区：
文献类型：
--
作者：
Goudas, Theodosis;Doukas, Charalampos;Maglogiannis, Ilias
生物医学图像数据的分析和表征是一个复杂的过程，涉及多个处理阶段，例如数据采集，预处理，分割，特征提取和分类。使用的方法的正确组合和参数化在很大程度上依赖于给定的图像数据集和实验类型。因此，他们可能需要从生物医学专家一边进行高级图像处理和分类知识和技能。在这项研究中，提出了一个应用程序，利用Web服务和应用本体论建模，以实现智能创建图像挖掘工作流程。所描述的工具可以直接集成到Rapidminer，Taverna或类似的工作流管理平台。提出了用于创建样品工作流程以分析肾脏活检显微镜图像的案例研究，以证明所提出的框架的功能。
The analysis and characterization of biomedical image data is a complex procedure involving several processing phases, such as data acquisition, preprocessing, segmentation, feature extraction, and classification. The proper combination and parameterization of the utilized methods are heavily relying on the given image dataset and experiment type. They may thus necessitate advanced image processing and classification knowledge and skills from the side of the biomedical expert. In this study, an application, exploiting web services and applying ontological modeling, is presented, to enable the intelligent creation of image-mining workflows. The described tool can be directly integrated to the RapidMiner, Taverna or similar workflow management platforms. A case study dealing with the creation of a sample workflow for the analysis of kidney biopsy microscopy images is presented to demonstrate the functionality of the proposed framework.