Comput. Biol. Med. - Effective FCM noise clustering algorithms in medical images.

Tópicos

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Resumo

The main motivation of this paper is to introduce a class of robust non-Euclidean distance measures for the original data space to derive new objective function and thus clustering the non-Euclidean structures in data to enhance the robustness of the original clustering algorithms to reduce noise and outliers. The new objective functions of proposed algorithms are realized by incorporating the noise clustering concept into the entropy based fuzzy C-means algorithm with suitable noise distance which is employed to take the information about noisy data in the clustering process. This paper presents initial cluster prototypes using prototype initialization method, so that this work tries to obtain the final result with less number of iterations. To evaluate the performance of the proposed methods in reducing the noise level, experimental work has been carried out with a synthetic image which is corrupted by Gaussian noise. The superiority of the proposed methods has been examined through the experimental study on medical images. The experimental results show that the proposed algorithms perform significantly better than the standard existing algorithms. The accurate classification percentage of the proposed fuzzy C-means segmentation method is obtained using silhouette validity index.

Resumo Limpo

main motiv paper introduc class robust noneuclidean distanc measur origin data space deriv new object function thus cluster noneuclidean structur data enhanc robust origin cluster algorithm reduc nois outlier new object function propos algorithm realiz incorpor nois cluster concept entropi base fuzzi cmean algorithm suitabl nois distanc employ take inform noisi data cluster process paper present initi cluster prototyp use prototyp initi method work tri obtain final result less number iter evalu perform propos method reduc nois level experiment work carri synthet imag corrupt gaussian nois superior propos method examin experiment studi medic imag experiment result show propos algorithm perform signific better standard exist algorithm accur classif percentag propos fuzzi cmean segment method obtain use silhouett valid index

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