Abstract

Image segmentation has been popularly performed for researchers in the field of Biomedical, Informatics Engineering, and Statistical Computation. This study tries to compare several methods for brain tumor image segmentation, especially in handling noise. The methods are K-means Cluster, Fuzzy C-Means (FCM) Cluster, Gaussian Mixture Model (GMM), and Fernandez-Steel Skew Normal (FSSN) Mixture model. K-means and FCM are the popular Partitioning methods for clustering, while GMM is model-based clustering method. The FSSN mixture model is the new model-based clustering introduced in this study. Both GMM and FSSN are formed through a finite mixture model with Bayesian Markov Chain Monte Carlo (MCMC) optimization. The dataset is the MRI brain tumor image from General Regional Hospital (RSUD) Dr. Soetomo Surabaya. Gaussian noise and Salt pepper noise are generated to see the robustness of each method. Various evaluation parameters like Silhouette Index, Partition Coefficient Index, and Misclassification Ratio are calculated for the appropriate methods and comparative analysis is carried out. The results indicate for partitioning methods especially FCM is more robust in handling Gaussian noise, while GMM is more robust in handling Salt and pepper noise. The outstanding result shows that the FSSN mixture model could handle both Gaussian and Salt pepper noise better than other methods.

Original languageEnglish
Title of host publication2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages289-293
Number of pages5
ISBN (Electronic)9781538675090
DOIs
Publication statusPublished - 2 Jul 2018
Event2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018 - Surabaya, Indonesia
Duration: 26 Nov 201827 Nov 2018

Publication series

Name2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018 - Proceeding

Conference

Conference2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018
Country/TerritoryIndonesia
CitySurabaya
Period26/11/1827/11/18

Keywords

  • Bayesian
  • FCM
  • Fernandez-Steel Skew Normal
  • GMM
  • K-means
  • image segmentation
  • mixture

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