Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain ; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain.
PLoS One. 2013 Aug 22;8(8):e70797. doi: 10.1371/journal.pone.0070797. eCollection 2013.
We present jClustering, an open framework for the design of clustering algorithms in dynamic medical imaging. We developed this tool because of the difficulty involved in manually segmenting dynamic PET images and the lack of availability of source code for published segmentation algorithms. Providing an easily extensible open tool encourages publication of source code to facilitate the process of comparing algorithms and provide interested third parties with the opportunity to review code. The internal structure of the framework allows an external developer to implement new algorithms easily and quickly, focusing only on the particulars of the method being implemented and not on image data handling and preprocessing. This tool has been coded in Java and is presented as an ImageJ plugin in order to take advantage of all the functionalities offered by this imaging analysis platform. Both binary packages and source code have been published, the latter under a free software license (GNU General Public License) to allow modification if necessary.
我们提出了 jClustering,这是一个用于设计动态医学成像中聚类算法的开放框架。我们开发这个工具是因为手动分割动态 PET 图像具有一定难度,并且发布的分割算法缺少源代码。提供一个易于扩展的开放工具可以鼓励发布源代码,从而促进算法比较的过程,并为感兴趣的第三方提供审查代码的机会。该框架的内部结构允许外部开发人员轻松快速地实现新算法,只需关注正在实现的方法的细节,而无需处理和预处理图像数据。该工具是用 Java 编写的,并作为 ImageJ 插件呈现,以利用该成像分析平台提供的所有功能。我们已经发布了二进制包和源代码,后者采用自由软件许可证(GNU 通用公共许可证)发布,以便在必要时进行修改。