Cellular automata segmentation of brain tumors on post contrast MR images

Hamamcı, Andaç and Ünal, Gözde and Küçük, Nadir and Engin, Kayıhan (2010) Cellular automata segmentation of brain tumors on post contrast MR images. In: 13th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2010), Beijing, China

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Official URL: http://dx.doi.org/10.1007/978-3-642-15711-0_18


In this paper, we re-examine the cellular automata(CA) al- gorithm to show that the result of its state evolution converges to that of the shortest path algorithm. We proposed a complete tumor segmenta- tion method on post contrast T1 MR images, which standardizes the VOI and seed selection, uses CA transition rules adapted to the problem and evolves a level set surface on CA states to impose spatial smoothness. Val- idation studies on 13 clinical and 5 synthetic brain tumors demonstrated the proposed algorithm outperforms graph cut and grow cut algorithms in all cases with a lower sensitivity to initialization and tumor type.

Item Type:Papers in Conference Proceedings
Subjects:Q Science > QA Mathematics > QA075 Electronic computers. Computer science
ID Code:15167
Deposited By:Gözde Ünal
Deposited On:22 Nov 2010 15:05
Last Modified:29 Jul 2019 11:17

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