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

Abstract

Background: During the two past decades, medical image fusion has become an essential part of
modern 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 of
the input images.
Methods: A new image fusion algorithm improves the visual quality of the fused image, based on
feature selection and Principal Component Analysis (PCA) in the Dual-Tree Complex Wavelet
Transform (DTCWT) domain. It is called Feature Selection with Principal Component Analysis
and Dual-Tree Complex Wavelet Transform (FSPCA-DTCWT). Using different fusion rules in a
single algorithm result in correctly reconstructed image (fused image), this combination will
produce a new technique, which employs the advantages of each method separately. The DTCWT
presents good directionality since it considers the edge information in six directions and provides
approximate 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 proposed
algorithm fuses the detailed wavelet coefficients of input images using features selection rule.
Results: Several experiments have been conducted over different sets of multimodal medical
images such as CT/MRI, MRA/T1-MRI. However, due to pages-limit on a paper, only results of
three sets have been presented. The FSPCA-DTCWT algorithm is compared to recent fusion
methods presented in the literature (eight methods) in terms of visual quality and quantitatively
using well-known fusion performance metrics (five metrics). Results showed that the proposed
algorithm outperforms the existing ones regarding visual and quantitative evaluations.
Conclusion: This paper focuses on medical image fusion of different modalities. A novel image
fusion algorithm based on DTCWT to merge multimodal medical images has been proposed.
Experiments have been performed using two different sets of multimodal medical images. The
results show that the proposed fusion method significantly outperforms the recent fusion
techniques reported in the literature.