Enhancement of brain tumor MR images based on intuitionistic fuzzy sets

Wankai Deng; He Deng; Lifang Cheng

doi:10.1117/12.2205334

14 December 2015 Enhancement of brain tumor MR images based on intuitionistic fuzzy sets

Wankai Deng, He Deng, Lifang Cheng

Author Affiliations +

Proceedings Volume 9814, MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing; 98140H (2015) https://doi.org/10.1117/12.2205334
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China

Abstract

Brain tumor is one of the most fatal cancers, especially high-grade gliomas are among the most deadly. However, brain tumor MR images usually have the disadvantages of low resolution and contrast when compared with the optical images. Consequently, we present a novel adaptive intuitionistic fuzzy enhancement scheme by combining a nonlinear fuzzy filtering operation with fusion operators, for the enhancement of brain tumor MR images in this paper. The presented scheme consists of the following six steps: Firstly, the image is divided into several sub-images. Secondly, for each sub-image, object and background areas are separated by a simple threshold. Thirdly, respective intuitionistic fuzzy generators of object and background areas are constructed based on the modified restricted equivalence function. Fourthly, different suitable operations are performed on respective membership functions of object and background areas. Fifthly, the membership plane is inversely transformed into the image plane. Finally, an enhanced image is obtained through fusion operators. The comparison and evaluation of enhancement performance demonstrate that the presented scheme is helpful to determine the abnormal functional areas, guide the operation, judge the prognosis, and plan the radiotherapy by enhancing the fine detail of MR images.

Citation Download Citation

Wankai Deng, He Deng, and Lifang Cheng "Enhancement of brain tumor MR images based on intuitionistic fuzzy sets", Proc. SPIE 9814, MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing, 98140H (14 December 2015); https://doi.org/10.1117/12.2205334

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