Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICIP.2004.1421669
Title: Medical image segmentation with minimal path deformable models
Authors: Yan, P.
Kassim, A.A. 
Issue Date: 2004
Source: Yan, P.,Kassim, A.A. (2004). Medical image segmentation with minimal path deformable models. Proceedings - International Conference on Image Processing, ICIP 4 : 2733-2736. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2004.1421669
Abstract: This paper presents an algorithm that segments medical images by extracting object contours. It delineates object boundaries by detecting a path with the minimum energy on the image. A worm algorithm based on deformable models is proposed to find the minimal path by using the dynamic programming technique. The proposed algorithm overcomes the shortcomings of traditional deformable models such as fastidious initialization and inefficiency on segmenting objects with complex shapes or topologies. After presenting the algorithm, its performance on various synthetic and medical images is shown. Experimental results indicate that the proposed algorithm is robust to noise and edge discontinuities. © 2004 IEEE.
Source Title: Proceedings - International Conference on Image Processing, ICIP
URI: http://scholarbank.nus.edu.sg/handle/10635/70912
ISBN: 0780385543
ISSN: 15224880
DOI: 10.1109/ICIP.2004.1421669
Appears in Collections:Staff Publications

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