Multi-Modality Medical Image Fusion Using Cross Bilateral Filter with Fuzzy Logic

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Harmeet Kaur
satish kumar

Abstract

The domain of Medical images is escalating with the trend of digital image based diagnosis and treatment. When talking about Tumors and Cancers, medical images play significant role to identify the affected area with maximum precision. In this paper, Cross Bilateral Filter is used to focus on retaining the edges. The Muti-Modality medical images are firstly decomposed using cross Bilateral Filter and Wavelets (in parallel), followed by fusion of detailed parts by Fuzzy Logic Infererence System having 25 set of rules and approximate parts are fused with average rule. Lastly, the reconstruction is done to obtain the final fused image. To compare the results quantitatively as well as qualitatively, MR-T1, MR-T2 images when fused with proposed method, attained higher values for Standard Deviation (SD), Fusion Symmetry (FS), Correlation Coefficient (CC) and QAB/F and lower value of NAB/F.

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How to Cite
Kaur, H., & satish kumar. (2020). Multi-Modality Medical Image Fusion Using Cross Bilateral Filter with Fuzzy Logic. INFOCOMP Journal of Computer Science, 19(2), 141–150. Retrieved from https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/1067
Section
Computer Graphics, Image Processing, Visualization and Virtual Reality