jClustering is a dynamic image clustering framework for ImageJ. It provides a public API for implementing new clustering algorithms and several implementations.
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README.md

Introduction

jClustering is a dynamic imaging clustering framework for ImageJ. It is not only a development API for automatic segmentation algorithms, but also a platform aimed at centralizing different implementations that as today are not available in either source code or binary download.

Reference

Mateos-Pérez JM, García-Villalba C, Pascau J, Desco M, Vaquero JJ (2013) jClustering, an Open Framework for the Development of 4D Clustering Algorithms. PLoS ONE 8(8): e70797. doi:10.1371/journal.pone.0070797. Link.

Contact

If you wish to develop your own techniques/metrics for jClustering and need help, or you wish to contribute your own code to this project, please do not hesitate to contact me at jmmateos@mce.hggm.es.

What is jClustering?

jClustering is an ImageJ plugin developed with the purpose of becoming a general framework for dynamic imaging clustering, such as dynamic PET segmentation. It consists of grouping together voxels with similar time-activity curves (TACs). jClustering is written in Java and provides a very simple API interface that will allow the implementation of new clustering algorithms in a short time. The fact that it is implemented on top of ImageJ gives it all the advantages of using an open-source imaging analysis platform.

Using jClustering

Please refer to the user manual for download, installation and usage instructions.

Developing for jClustering

If you want to use jClustering as the platform to implement your own clustering algorithms, please refer to the developer manual for a brief development guide. If you have any questions, please do not hesitate to ask.

External tools

As an independent project that intends to add more advanced dynamic imaging capabilities to ImageJ, you might want to try the LIM Tools plugin. It adds several tools to mask dynamic studies, create average images and explore the time-activity curves, for example.