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.
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.
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 firstname.lastname@example.org.
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.
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.
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.