Gala is a Python library for performing and evaluating image segmentation, distributed under the open-source, BSD-like Janelia Farm license. It implements the algorithm described in Nunez-Iglesias et al., PLOS ONE, 2013.
If you use code from this library in your research, please cite:
Nunez-Iglesias J, Kennedy R, Plaza SM, Chakraborty A and Katz WT (2014) Graph-based active learning of agglomeration (GALA): a Python library to segment 2D and 3D neuroimages. Front. Neuroinform. 8:34. doi:10.3389/fninf.2014.00034
If you use or compare to the GALA algorithm in your research, please cite:
Nunez-Iglesias J, Kennedy R, Parag T, Shi J, Chklovskii DB (2013) Machine Learning of Hierarchical Clustering to Segment 2D and 3D Images. PLoS ONE 8(8): e71715. doi:10.1371/journal.pone.0071715
BibTeX entries of the above two papers are available in the file "CITATION.bib".
@article{gala-frontiers, Author="Nunez-Iglesias, Juan AND Kennedy, Ryan AND Plaza, Stephen M. AND Chakraborty, Anirban AND Katz, William T. ", Title="{{G}raph-based active learning of agglomeration ({G}{A}{L}{A}): a {P}ython library to segment 2{D} and 3{D} neuroimages}", Journal="Front Neuroinform", Year="2014", Volume="8", Pages="34", url={http://journal.frontiersin.org/article/10.3389/fninf.2014.00034/abstract}, doi={10.3389/fninf.2014.00034} }
@article{gala-plosone, author={Nunez-Iglesias, Juan AND Kennedy, Ryan AND Parag, Toufiq AND Shi, Jianbo AND Chklovskii, Dmitri B.}, Title="{{M}achine learning of hierarchical clustering to segment 2{D} and 3{D} images}", Journal="PLoS ONE", Year="2013", Volume="8", Number="8", Pages="e71715", url={{http://dx.doi.org/10.1371%2Fjournal.pone.0071715}}, doi={10.1371/journal.pone.0071715} }