ImageJ plugin for the Snell segmentation method

0438902 - ÚTIA 2015 RIV BE eng O - Others
Schier, Jan
ImageJ plugin for the Snell segmentation method.
2014
R&D Projects: GA TA ČR TA01010931
Institutional support: RVO:67985556
Keywords : Image Processing * Image Segmentation * ImageJ plugin
Subject RIV: JC - Computer Hardware ; Software

For image segmentation in the bioimaging field, the Otsu thresholding algorithm is very often the algorithm of choice. It's simple and fast algorithm. The drwaback of this algorithm is that it does not account for the image contents, and, in the bioimaging context, it often sets the threshold too high. In result, the contours of the resulting binary objects do not fully cover the original objects. An alternative option is represented by algorithms based on iterative optimization, such as the active contours, deformable models, etc. These algorithms are iterative and possibly rather computationally expensive. An interesting trade-off between the two approaches has been described in Snell et al: Segmentation and shape classification of nuclei in DAPI images. This method uses cost function that relates to the quality of resulting boundary. In the poster, an implementation of the Snell algorithm in the form of an ImageJ plugin was presented.
Permanent Link: http://hdl.handle.net/11104/0243123