Efficient Brain and Liver Tumor Segmentation using Seagull Optimization Algorithm based Super Pixel Fuzzy Clustering

被引：0

作者：

Devi, S. Nandhini ^{[1
]}

Manoharan, E. Gnana ^{[1
]}

机构：

[1] Annamalai University, Department of Electronics and Communication Engineering, Chidambaram, India

来源：

3rd International Conference on Smart Electronics and Communication, ICOSEC 2022 - Proceedings | 2022年

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Brain - Cluster analysis - Computer aided diagnosis - Fuzzy clustering - Image segmentation - K-means clustering - Magnetic resonance imaging - Medical imaging - Optimization - Pixels - Tumors

引用

页码：930 / 940

共 3 条

[1] Brain Tumor Segmentation Using Fuzzy Otsu Threshold Morphological Algorithm
Wisaeng, K.
Sa-ngiamvibool, W.
IAENG International Journal of Applied Mathematics, 2023, 53 (02):
[2] Oppositional based Seagull Optimization Algorithm based 3D DCNN for Medical Image Semantic Segmentation
Tapasvi, B.
Gnana, E.
Udaya, N.
6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022 - Proceedings, 2022, : 695 - 704
[3] An Efficient Scyphozoa Swarm Optimization and Fuzzy Density Based Clustering Routing for Underwater Wireless Sensor Networks
Kavitha, R.J.
Anandavalli, P.
Tehnicki Vjesnik, 2024, 31 (05): : 1589 - 1595

← 1 →