On active contour models and balloons
CVGIP: Image Understanding
A Robust Snake Implementation; A Dual Active Contour
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gradient Vector Flow: A New External Force for Snakes
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Deformable models with application to human cerebral cortex reconstruction from magnetic resonance images
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Automatic fuzzy-neural based segmentation of microscopic cell images
MDA'06/07 Proceedings of the 2007 international conference on Advances in mass data analysis of signals and images in medicine biotechnology and chemistry
Cell microscopic segmentation with spiking neuron networks
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
A two-level method for segmenting cytological images based on active contour model
Pattern Recognition and Image Analysis
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This paper presents a semi-automatic method for segmentation of digital images. The segmentation method is based on snakes and a novel implementation of the snake evolution algorithm is presented. Analytical expressions describing the snake evolution are derived using the Fourier transform. These expressions can be sampled and used in a fast algorithm for snake propagation. Experiments are carried out on images of histopathological tissue sections and the results are very promising. In particular the method is able to cope with overlapping nuclei.