Automated Brain Tumor Segmentation on MR Images Based on Neutrosophic Set Approach

被引：0

作者：

Mohan, J. ^{[1
]}

Krishnaveni, V ^{[2
]}

Huo, Yanhui ^{[3
]}

机构：

[1] Vignan Univ, Dept Elect & Commun Engn, Vadlamudi 522213, Andhra Prades, India

[2] PSG Coll Technol, Dept Elect & Commun Engn, Coimbatore 641004, Tamil Nadu, India

[3] St Thomas Univ, Sch Sci Technol & Engn Management, Miami Gardens, FL 33054 USA

来源：

2015 2ND INTERNATIONAL CONFERENCE ON ELECTRONICS AND COMMUNICATION SYSTEMS (ICECS) | 2015年

关键词：

Brain Tumor; k-means clustering; Magnetic Resonance Imaging; Neutrosophic Set; Wiener; FUZZY CONNECTEDNESS; FRAMEWORK;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Brain tumor segmentation for MR images is a difficult and challenging task due to variation in type, size, location and shape of tumors. This paper presents an efficient and fully automatic brain tumor segmentation technique. This proposed technique includes non local preprocessing, fuzzy intensification to enhance the quality of the MR images, k - means clustering method for brain tumor segmentation. The results are evaluated based on accuracy, sensitivity, specificity, false positive rate, false negative rate, Jaccard similarity metric and Dice coefficient. The preliminary results show 100% detection rate in all 20 test sets.

引用

页码：1078 / 1083

页数：6

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