Brain MRI tumor image fusion combined with Shearlet and wavelet

Changjiang Zhang; Mingchao Fang

doi:10.1117/12.2287095

15 November 2017 Brain MRI tumor image fusion combined with Shearlet and wavelet

Changjiang Zhang, Mingchao Fang

Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 1060517 (2017) https://doi.org/10.1117/12.2287095
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China

Abstract

In order to extract the effective information in different modalities of the tumor region in brain Magnetic resonance imaging (MRI) images, we propose a brain MRI tumor image fusion method combined with Shearlet and wavelet transform. First, the source images are transformed into Shearlet domain and wavelet domain. Second, the low frequency component of Shearlet domain is fused by Laplace pyramid decomposition. Then the low-frequency fusion image is obtained through inverse Shearlet transform. Third, the high frequency subimages in wavelet domain are fused. Then the high-frequency fusion image is obtained through inverse wavelet transform. Finally, the low-frequency fusion image and high-frequency fusion image are summated to get the final fusion image. Through experiments conducted on 10 brain MRI tumor images, the result shown that the proposed fusion algorithm has the best fusion effect in the evaluation indexes of spatial frequency, edge strength and average gradient. The main spatial frequency of 10 images is 29.22, and the mean edge strength and average gradient is 103.77 and 10.42. Compared with different fusion methods, we find that the proposed method effectively fuses the information of multimodal brain MRI tumor images and improves the clarity of the tumor area well.

Citation Download Citation

Changjiang Zhang and Mingchao Fang "Brain MRI tumor image fusion combined with Shearlet and wavelet", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 1060517 (15 November 2017); https://doi.org/10.1117/12.2287095

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available