ITKGrowCut is a remote module for ITK. The main filter segments a 3D image from user-provided seeds.

The original idea was presented by Vezhnevets and Konouchine:

Vladimir Vezhnevets and Vadim Konouchine:

“GrowCut” – interactive multi-label N-D image segmentation by cellular automata.

In: Proc. Graphicon. (2005) 150–156

In 2011 Harini Veeraraghavan of Memorial Sloan Kettering Cancer Center provided an implementation based on ITK.

In 2014, Zhu et al. presented an efficient approximation:

Liangjia Zhu, Ivan Kolesov, Yi Gao, Ron Kikinis, Allen Tannenbaum.

An Effective Interactive Medical Image Segmentation Method Using Fast GrowCut

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI),

Interactive Medical Image Computing Workshop, 2014

Zhu et al. also provided an open source implementation as a Slicer plugin, based on VTK. Since then, their implementation was integrated into Slicer, refactored and improved. In this remote module we are building upon the improved variant from Slicer.

This software was developed in part by the Center for Integrative Biomedical Computing (CIBC), the Scientific Computing and Imaging (SCI) Institute and Kitware.

Support came from the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH) under grant numbers P41 GM103545 and R24 GM136986.