Multimodal medical image fusion based on yager’ s intuitionistic fuzzy sets

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Tirupal T.; Chandra Mohan B.; Srinivas Kumar S.

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Journal: Iranian Journal of Fuzzy Systems Year:2019 | Volume:16 | Issue:1 Page(s): 33-48

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Information Journal Paper

Title

Multimodal medical image fusion based on yager’ s intuitionistic fuzzy sets

Author(s)

Tirupal T. | Chandra Mohan B. | Srinivas Kumar S. | Issue Writer Certificate

Keywords

Image fusionQ2

Intuitionistic fuzzy setsQ2

Multimodal medical imagesQ2

Intuitionistic fuzzy entropyQ2

Decision mapQ2

Abstract

The objective of Image fusion for medical images is to combine multiple images obtained from various sources into a single image suitable for better diagnosis. Most of the state-of-the-art image fusing technique is based on nonfuzzy sets, and the fused image so obtained lags with complementary information. Intuitionistic fuzzy sets (IFS) are determined to be more suitable for civilian, and medical image processing as more uncertainties are considered compared with fuzzy set theory. In this paper, an algorithm for effectively fusing Multimodal medical images is presented. In the proposed method, images are initially converted into Yager’ s intuitionistic fuzzy complement images (YIFCIs), and a new objective function called Intuitionistic fuzzy entropy (IFE) is employed to obtain the optimum value of the parameter in membership and non-membership functions. Next, the YIFCIs are compared using contrast visibility (CV) to construct a Decision map (DM). DM is refined with consistency verification to create a fused image. Simulations on several pairs of Multimodal medical images are performed and compared with the existing fusion methods, such as simple average, discrete cosine transform (DCT), redundant wavelet transform (RWT), intuitionistic fuzzy set, fuzzy transform and interval-valued intuitionistic fuzzy set (IVIFS). The superiority of the proposed method is presented and is justified. Fused image quality is also verified with various quality metrics, such as spatial frequency (SF), average gradient (AG), fusion symmetry (FS), edge information preservation (QAB=F ), entropy (E) and computation time (CoT).

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APA: Copy

Tirupal, T., Chandra Mohan, B., & Srinivas Kumar, S.. (2019). Multimodal medical image fusion based on yager’ s intuitionistic fuzzy sets. IRANIAN JOURNAL OF FUZZY SYSTEMS, 16(1 ), 33-48. SID. https://sid.ir/paper/113236/en

Vancouver: Copy

Tirupal T., Chandra Mohan B., Srinivas Kumar S.. Multimodal medical image fusion based on yager’ s intuitionistic fuzzy sets. IRANIAN JOURNAL OF FUZZY SYSTEMS[Internet]. 2019;16(1 ):33-48. Available from: https://sid.ir/paper/113236/en

IEEE: Copy

T. Tirupal, B. Chandra Mohan, and S. Srinivas Kumar, “Multimodal medical image fusion based on yager’ s intuitionistic fuzzy sets,” IRANIAN JOURNAL OF FUZZY SYSTEMS, vol. 16, no. 1 , pp. 33–48, 2019, [Online]. Available: https://sid.ir/paper/113236/en

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