کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6901327 | 1446493 | 2017 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
D-FCM: Density based fuzzy c-means clustering algorithm with application in medical image segmentation
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Fuzzy c-means algorithm (FCM) is a powerful clustering algorithm and it is widely used in image segmentation. However, in FCM, we need to give both the parameters of the number of clusters and the initial membership matrix in advance, and they affect the clustering performance heavily. In this paper, we propose a novel density based fuzzy c-means algorithm (D-FCM) by introducing density for each sample. The density peaks are used to determine the number of clusters and the initial membership matrix automatically. Experimental results on benchmark datasets and medical image segmentation datasets show the efficiency and effectiveness of our D-FCM.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 122, 2017, Pages 407-414
Journal: Procedia Computer Science - Volume 122, 2017, Pages 407-414
نویسندگان
Hua-Xin Pei, Zeng-Rong Zheng, Chen Wang, Chun-Na Li, Yuan-Hai Shao,