Center for Biomedical Imaging & Informatics, UMDNJ-Robert Wood Johnson Medical School, New Brunswick, New Jersey 08901, USA.
J Am Med Inform Assoc. 2011 Jul-Aug;18(4):403-15. doi: 10.1136/amiajnl-2011-000170. Epub 2011 May 23.
The design and implementation of ImageMiner, a software platform for performing comparative analysis of expression patterns in imaged microscopy specimens such as tissue microarrays (TMAs), is described. ImageMiner is a federated system of services that provides a reliable set of analytical and data management capabilities for investigative research applications in pathology. It provides a library of image processing methods, including automated registration, segmentation, feature extraction, and classification, all of which have been tailored, in these studies, to support TMA analysis. The system is designed to leverage high-performance computing machines so that investigators can rapidly analyze large ensembles of imaged TMA specimens. To support deployment in collaborative, multi-institutional projects, ImageMiner features grid-enabled, service-based components so that multiple instances of ImageMiner can be accessed remotely and federated.
The experimental evaluation shows that: (1) ImageMiner is able to support reliable detection and feature extraction of tumor regions within imaged tissues; (2) images and analysis results managed in ImageMiner can be searched for and retrieved on the basis of image-based features, classification information, and any correlated clinical data, including any metadata that have been generated to describe the specified tissue and TMA; and (3) the system is able to reduce computation time of analyses by exploiting computing clusters, which facilitates analysis of larger sets of tissue samples.
描述了用于对组织微阵列（TMA）等成像显微镜标本的表达模式进行比较分析的软件平台 ImageMiner 的设计和实现。ImageMiner 是一个联邦服务系统，为病理学研究中的调查研究应用程序提供了可靠的分析和数据管理功能集。它提供了一系列图像处理方法，包括自动配准、分割、特征提取和分类，所有这些方法在这些研究中都经过了定制，以支持 TMA 分析。该系统旨在利用高性能计算机会，以便研究人员可以快速分析大量成像的 TMA 标本。为了支持协作式、多机构项目的部署，ImageMiner 具有基于网格的、基于服务的组件，因此可以远程访问和联合多个实例的 ImageMiner。
实验评估表明：（1）ImageMiner 能够支持对成像组织内肿瘤区域的可靠检测和特征提取；（2）可以根据基于图像的特征、分类信息以及任何相关的临床数据（包括用于描述指定组织和 TMA 的任何元数据）搜索和检索在 ImageMiner 中管理的图像和分析结果；（3）该系统能够通过利用计算集群来减少分析的计算时间，从而方便对更大的组织样本集进行分析。
