# Hypersnakuscules

### Description

Hypersnakuscules provide an efficient and highly parallel algorithm for evolving spherically symmetric three-dimensional contours. This work extends previous work from EPFL on fast two-dimensional snakes [2]. This formulation is  optimized for 3D images, and includes a strategy for GPU acceleration that takes advantage of Monte-Carlo sampling. Experimental results show that this method provides superior performance for large 2D and 3D cell localization tasks when compared to existing methods on large 3D brain images.

### Usage

Hypersnakuscules takes as input a 3D RAW image, along with the image size:

>> hypersnakuscules input.raw output.txt --size x y z

The output file output.txt gives the  coordinates for each surviving snake, as well as its radius. A full list of command-line options can be listed using:
>> hypersnakuscules --help

### References

[ 1 ] Mahsa Lotfollahi, Sebastian Berisha, Leila Saadatifard, Laura Montier, Jokūbas Žiburkus, David Mayerich, "Three-Dimensional GPU-Accelerated Active Contours for Automated Localization of Cells in Large Images," PLoS ONE (in press)

[ 2 ] Philippe Thevenaz, Michael Unser, "Snakuscules," IEEE Transactions on Image Processing, 17(4):585-593, 14 March 2008