Red Piranha Optimization Based Fast and Robust Fuzzy C-Means Clustering for Precise Glioma Segmentation in Therapeutic Applications

G, Sophia and Ramaraj, Kottaimalai and K, Karthikeyan and Surendhar S, Prasath Alias and B, Ambika and M, Thilagaraj (2024) Red Piranha Optimization Based Fast and Robust Fuzzy C-Means Clustering for Precise Glioma Segmentation in Therapeutic Applications. In: UNSPECIFIED.

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Abstract

Gliomas resemble glial cells and are the most common brain tumors. Treatment includes chemotherapy, radiation, and sometimes surgery. Accurate MRI-based segmentation is vital for planning and diagnosis. This study uses an integrated segmentation algorithm combining Fuzzy C-Means (FCM) clustering and Red Piranha Optimization (RPO). FRFCM improves traditional FCM limitations. Evaluations on BraTS datasets show enhanced Dice score of 92%, aiding clinical decisions.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Science > Computer Science
Divisions: Arts and Science > Vinayaka Mission's Kirupananda Variyar Arts & Science College, Salem > Computer Science
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 27 Nov 2025 06:46
URI: https://vmuir.mosys.org/id/eprint/1775

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