Please use this identifier to cite or link to this item:
https://dspace.univ-ouargla.dz/jspui/handle/123456789/37119
Title: | Medical Image Segmentation Using Multikernel Method |
Authors: | NASRI, NADGIB Djari, Abdennour |
Keywords: | Multi-Kernel Fuzzy C-Means Segmentation Medical Image |
Issue Date: | 2024 |
Publisher: | UNIVERSITY OF KASDI MERBAH OUARGLA |
Citation: | FACULTY OF NEW TECHNOLOGIES OF INFORMATION AND COMMUNICATION |
Abstract: | “This work introduces the Multi-Kernel Fuzzy C-Means (MKFCM) algorithm for medical image segmentation, demonstrating its superior performance over traditional Fuzzy C-Means (FCM) and Kernel Fuzzy C-Means (KFCM). By integrating multiple kernels, MKFCM effectively handles complex data distributions, noise, achieving higher accuracy and robustness. Quantitative evaluations using Dice Coefficient and Intersection over Union (IOU) scores confirm MKFCM's enhanced segmentation capabilities, making it a highly effective tool for precise medical imaging.” |
Description: | Automation and Systems |
URI: | https://dspace.univ-ouargla.dz/jspui/handle/123456789/37119 |
Appears in Collections: | Département d'Electronique et des Télécommunications - Master |
Files in This Item:
File | Description | Size | Format | |
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DJARI.pdf | Automation and Systems | 2,73 MB | Adobe PDF | View/Open |
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