Nov 18, 2014 · The FEC algorithm provides better segmentation result for noise free images and retains more image information during clustering application.

The efficacy of IFEC algorithm is demonstrated by comparing it quantitatively with the state-of-the-art segmentation approaches in terms of similarity index on ...

Mar 25, 2021 · The steps of the FCM-based image segmentation algorithm are as follows: (1) Input the brain MRI image; (2) set the fuzzy factor m = 2, the ...

In this article, we have proposed an improved fuzzy entropy clustering (IFEC) algorithm by introducing a new fuzzy factor, which incorporates both local spatial ...

This article describes a new clustering method for segmentation of Magnetic resonance imaging (MRI) brain images.

Across various image slices, the PSO-GWO method consistently outperforms FCM in terms of accuracy, showing improvements ranging from 1.28% to 1.46%, ...

This article describes a new clustering method for segmentation of Magnetic resonance imaging (MRI) brain images.

In this article, we have proposed an improved fuzzy entropy clustering (IFEC) algorithm by introducing a new fuzzy factor, which incorporates both local spatial ...

We propose a new fuzzy clustering algorithm by incorporating constrained class uncertainty-based entropy for brain MR image segmentation. Due to deficiencies of ...

The KFCOM and WKFCOM algorithms are used to analyze the brain MRI images, and the KFCOM algorithm is quantitatively evaluated to have a lower error rate.