Medical Image Segmentation Using Fuzzy Clustering and Kernelized Fuzzy Clustering Algorithms

MATLAB 4.74M 248 views 0 downloads 1 credits
Tags:

Resource Overview

Implementation of medical image segmentation using fuzzy clustering and kernelized fuzzy clustering algorithms, developed in MATLAB with an optimized GUI for enhanced usability and visualization.

Detailed Documentation

To achieve improved medical image segmentation, we employ fuzzy clustering algorithms and their kernelized variants. These methods are implemented through MATLAB programming, which allows for efficient computation of cluster centroids and membership degrees using functions like fcm() for standard fuzzy C-means. The kernelized approach enhances segmentation accuracy by mapping data to higher-dimensional spaces via radial basis function (RBF) kernels. Additionally, a well-designed graphical user interface (GUI) is integrated using MATLAB's App Designer, enabling intuitive parameter adjustment (e.g., cluster count, kernel parameters) and real-time visualization of segmentation results through image processing toolboxes like Image Processing Toolbox for thresholding and region analysis.

You May Also Like