MRI Image Segmentation using Fuzzy C-Means in MATLAB

Open Access
Conference Proceedings
Authors: Brisaac JohnsonChris Crawford

Abstract: Image segmentation is challenging because an image has to be partitioned into regions with pixels that contain similar attributes. To accomplish this task, many use MATLAB, Python, or other environments that allow them to set thresholds for the image, to group similar pixels together, or remove undesirable pixels from the image. When approaching the image segmentation problem, many use the fuzzy c-means algorithm to group similar pixels with the same features in an image. Hence, it makes it easier to analyze specific areas in the image, such as a tumor that may be present. This paper presents a tutorial on performing image segmentation using MATLAB and Fuzzy C-Means. Through this tutorial, we examine how fuzzy c-mean is used to solve the image segmentation problem and the methodologies used to properly cluster data.

Keywords: MATLAB, Fuzzy C, Means, MRI, Image segmentation, tumor analysis, Machine Learning

DOI: 10.54941/ahfe1003026

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