Open AccessGuided filter‐based images fusion algorithm for CT and MRI medical images
Author(s) -
Na Yan,
Zhao Li,
Yang Yingxue,
Ren Mengqiao
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2016.0920
Subject(s) - algorithm , image fusion , wavelet , filter (signal processing) , wavelet transform , artificial intelligence , mathematics , medical imaging , magnetic resonance imaging , computer science , image (mathematics) , computer vision , medicine , radiology
A novel fusion algorithm based on guided filter (GF) for computed tomography (CT) and magnetic resonance imaging (MRI) medical images is proposed. In this algorithm: approximation coefficient and three wavelet coefficients of CT and MRI are obtained by the wavelet transform, respectively. Two weight maps are obtained by comparison of the pixel values of the two approximation coefficients. A GF is designed with the weight maps serving as the input image and the corresponding approximation coefficient serving as the guided image; the GF is used to smooth the weight images and refined weight maps are obtained. The approximation and wavelet coefficients of CT and MRI images are fused by the weighted fusion algorithm with refined weight maps. A fused image of CT and MRI is obtained by the inverse wavelet transform. Comparisons of this algorithm with two fusion algorithms available show that the fused image based on this algorithm contains a greater amount of information, more details and clearer edges than the other two algorithms. Therefore, this algorithm is better at locating the position and shape of the target volume. In the course of treatment, this algorithm can better avoid the surrounding health organs by radiation, protect the health of patients.