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Clustering of MRI in Brain Images Using Fuzzy C Means Algorithm

Habib, Md.R., Suhan, A.Y., Vadher, A., Swapno, Md.A.R., Arefin, Md.R., Islam, S., Rahman, K.A. and Tanvir, Md.S. (2022) Clustering of MRI in Brain Images Using Fuzzy C Means Algorithm. In: International Conference on Machine Learning and Autonomous Systems (ICMLAS) 2021, 24 - 25 September 2021, Kanyakumari, India pp. 437-448.

Link to Published Version: https://doi.org/10.1007/978-981-16-7996-4_31
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Abstract

This paper concentrates on the analyses of medical images of patients with brain tumor obtained via magnetic resonance imaging (MRI). Clustering algorithms, statistical techniques and various distribution functions are used to find patterns in the computed parameters to help finding the desired clustering technique. In this paper, Fuzzy C Means clustering algorithm is applied for each patient, and the negative functions and the iteration counts are noted. All simulations are carried out in MATLAB. The results reveal the objective functions and the iteration count of pre-operation and post-operation stages of MRI image frames. The thresholding method and multiple histograms are used to observe the images. An overview of how imaging techniques and MRI functions work is also reviewed along with the different medical image processing established methods.

Item Type: Conference Paper
Other Information: Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 269)
URI: http://researchrepository.murdoch.edu.au/id/eprint/64120
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