Segmentation of brain tumours for radiosurgery appl ications using image processing

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Year 2015 Vol 4 Issue 1
Document Type : original article
¹Madhuri R*
¹Department of Bioinformatics, VTU University, Bangalo re-560085, Karnataka, India. *Present Address: DBT-BIF Centre, Maharani Lakshmi Amm anni College For Women, Science Post, Bangalore-56001 2
Abstract
The proposed work is to segment the solid tumours w ith user interaction to assist researchers in Radiosurgery planning. The brain tumour segmentation methods rely on the intensity enhancement.

n this work, Cellular Automaton (CA) based seeded tumour segmentat ion algorithm is proposed. Which determine the Volu me of Interest (VOI) and seed selection is done based on the user interaction.
First, establish the connection of the CA-based segmentation to the Tumour-cut method to show that the iterative CA framework solves the shortest path complication. In that regard, the proposed method modify the state transi tion function of the CA to calculate the shortest pa th solution. Furthermore, an algorithm based on CA is presented to differentiate necrotic and enhancing tumour tissue content, which gains importance for a researcher in planning therapy response. The tumour -cut algorithm run twice for background seed (healt hy cell) and foreground seed (tumour cell) for probability calculation. Amo ng them, a clustering method have been investigated and used. Conclusion: Finally, this paper applied Tumour-Cut method and K -means clustering to differentiate necrotic and enh ancing tumour tissue content, which gains importance for a complete eval uation
Keywords
Keywords : Tumour-cut Cellular Automata (CA) interactive image segmentation k-means Necrotic region tumou
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