An Efficient Algorithm for Multimodal Medical Image Fusion based on Feature Selection and PCA Using DTCWT (FSPCA-DTCWT)

Journal Title: UNKNOWN - Year 2018, Vol 2, Issue 1

Abstract

Background: During the two past decades, medical image fusion has become an essential part ofmodern medicine due to the availability of numerous imaging modalities (e.g., MRI, CT, SPECT,etc.). This paper presents a new medical image fusion algorithm based on PCA and DTCWT,which uses different fusion rules to obtain a new image containing more information than any ofthe input images.Methods: A new image fusion algorithm improves the visual quality of the fused image, based onfeature selection and Principal Component Analysis (PCA) in the Dual-Tree Complex WaveletTransform (DTCWT) domain. It is called Feature Selection with Principal Component Analysisand Dual-Tree Complex Wavelet Transform (FSPCA-DTCWT). Using different fusion rules in asingle algorithm result in correctly reconstructed image (fused image), this combination willproduce a new technique, which employs the advantages of each method separately. The DTCWTpresents good directionality since it considers the edge information in six directions and providesapproximate shift invariant. The main goal of PCA is to extract the most significant characteristics(represented by the wavelet coefficients) in order to improve the spatial resolution. The proposedalgorithm fuses the detailed wavelet coefficients of input images using features selection rule.Results: Several experiments have been conducted over different sets of multimodal medicalimages such as CT/MRI, MRA/T1-MRI. However, due to pages-limit on a paper, only results ofthree sets have been presented. The FSPCA-DTCWT algorithm is compared to recent fusionmethods presented in the literature (eight methods) in terms of visual quality and quantitativelyusing well-known fusion performance metrics (five metrics). Results showed that the proposedalgorithm outperforms the existing ones regarding visual and quantitative evaluations.Conclusion: This paper focuses on medical image fusion of different modalities. A novel imagefusion algorithm based on DTCWT to merge multimodal medical images has been proposed.Experiments have been performed using two different sets of multimodal medical images. Theresults show that the proposed fusion method significantly outperforms the recent fusiontechniques reported in the literature.

Authors and Affiliations

Abdallah Bengueddoudj, Zoubeida Messali

Keywords

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  • EP ID EP648615
  • DOI 10.26415/2572-004X-vol2iss1p179-192
  • Views 26
  • Downloads 0

How To Cite

Abdallah Bengueddoudj, Zoubeida Messali (2018). An Efficient Algorithm for Multimodal Medical Image Fusion based on Feature Selection and PCA Using DTCWT (FSPCA-DTCWT). UNKNOWN, 2(1), 179-192. https://europub.co.uk/articles/-A-648615