1 research outputs found
Analisis Komputasi pada Segmentasi Citra Medis Adaptif Berbasis Logika Fuzzy Teroptimasi
The objective of this research is to analyze the computation of medical image adaptive
segmentation based on optimized fuzzy logic. The success of the image analysis system depends
on the quality of the segmentation. The image segmentation is separating the image into regions
that are meaningful for a given purpose. In this research, the Fuzzy C-Means (FCM) algorithm
with spatial information is presented to segment Magnetic Resonance Imaging (MRI) medical
images. The FCM clustering utilizes the distance between pixels and cluster centers in the
spectral domain to compute the membership function. The pixels of an object in image are
highly correlated, and this spatial information is an important characteristic that can be used to
aid their labeling. This scheme greatly reduces the effect of noise. The FCM method successfully
classifies the brain MRI images into five clusters. This technique is therefore a powerful method
in computationfor noisy image segmentation.
Keywords: computation analysis, MRI Medical image, adaptive image segmentation, fuzzy cmean