jClustering, an open framework for the development of 4D clustering algorithms

PLoS One. 2013 Aug 22;8(8):e70797. doi: 10.1371/journal.pone.0070797. eCollection 2013.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Brain / pathology
  • Cluster Analysis
  • Computer Graphics*
  • Contrast Media / chemistry
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Internet
  • Magnetic Resonance Imaging
  • Positron-Emission Tomography
  • Principal Component Analysis
  • Programming Languages*
  • Software
  • User-Computer Interface

Substances

  • Contrast Media

Grants and funding

Funded by TEC2011-28972-C02-01, Ministerio de Ciencia e Innovación, CEN-20101014; Programa CENIT-CDTI, Ministerio de Ciencia e Innovación; S2009/DPI-1802 (ARTEMIS), Comunidad de Madrid. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.