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Fahmi Jafargholkhanloo, Ali, Shamsi, Mousa, Bashiri Bawil, Mahdi. (1403). Robust Gustafson-Kessel (RGK) Clustering for Segmentation of Brain Tissues Based on MRI images. فیزیولوژی و بیوتکنولوژی آبزیان, (), -. doi: 10.22124/cse.2025.28776.1088
Ali Fahmi Jafargholkhanloo; Mousa Shamsi; Mahdi Bashiri Bawil. "Robust Gustafson-Kessel (RGK) Clustering for Segmentation of Brain Tissues Based on MRI images". فیزیولوژی و بیوتکنولوژی آبزیان, , , 1403, -. doi: 10.22124/cse.2025.28776.1088
Fahmi Jafargholkhanloo, Ali, Shamsi, Mousa, Bashiri Bawil, Mahdi. (1403). 'Robust Gustafson-Kessel (RGK) Clustering for Segmentation of Brain Tissues Based on MRI images', فیزیولوژی و بیوتکنولوژی آبزیان, (), pp. -. doi: 10.22124/cse.2025.28776.1088
Fahmi Jafargholkhanloo, Ali, Shamsi, Mousa, Bashiri Bawil, Mahdi. Robust Gustafson-Kessel (RGK) Clustering for Segmentation of Brain Tissues Based on MRI images. فیزیولوژی و بیوتکنولوژی آبزیان, 1403; (): -. doi: 10.22124/cse.2025.28776.1088

Robust Gustafson-Kessel (RGK) Clustering for Segmentation of Brain Tissues Based on MRI images

Computational Sciences and Engineering
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 17 بهمن 1403
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22124/cse.2025.28776.1088
نویسندگان
Ali Fahmi Jafargholkhanloo* 1؛ Mousa Shamsi2؛ Mahdi Bashiri Bawil3
1Department of Engineering Sciences, Faculty of Advanced Technologies, University of Mohaghegh Ardabili, Namin, Iran
2Faculty of Biomedical Engineering, Sahand University of Technology< Tabriz, Iran
3Faculty of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran.
چکیده
The fuzzy c-means (FCM) algorithm is widely used for image segmentation based on clustering. However, it is sensitive to noise, and its convergence is affected by the data distribution. FCM relies on the Euclidean distance metric, which fails to account for variations in the distances within similar and compact clusters. Moreover, the distance metric is not locally adaptive to the shape of clusters. This paper introduces a robust Gustafson-Kessel (RGK) clustering algorithm to address these limitations for brain tissue segmentation using MRI images. To achieve accurate segmentation under varying noise levels and intensity non-uniformity (INU), a Wiener filter integrated with wavelet transform (WFWT) is employed as a preprocessing step to enhance image quality while preserving object edges. The Mahalanobis distance is used for clustering to better adapt to the shape of the clusters. Additionally, the RGK algorithm incorporates membership matrix filtering to exploit the local spatial constraint. The proposed RGK algorithm was evaluated using two datasets: the BrainWeb simulated dataset and MRI scans from 10 healthy individuals at the Golghasht Medical Imaging Center in Tabriz (GMICT), Iran. In RGK, it is not necessary to compute the distance between pixels within local spatial neighbors and clusters. Experimental results demonstrate that the RGK algorithm outperforms traditional FCM-based methods in the segmentation of brain tissues.
کلیدواژه‌ها
Brain MRI Segmentation؛ Fuzzy c-means؛ Gustafson-Kessel؛ Image Segmentation؛ Wiener Filter
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تعداد مشاهده مقاله: 28


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