Paper Info
Title
Determination of benign and malign lesions by fusion of the different phases of liver MR.
Abstract
In this study, different phases of T1-weighted, dynamic contrast-enhanced liver magnetic resonance (MR) images were combined with wavelet-based image fusion to support decisions of radiologists. Used images has labelled as 6 different focal lesion types which focal nodular hyperplasia (FNH), hemangioma, cyst, colangiocellular carcinoma (CCC), hepatocellular carcinoma (HCC) and liver metastases. In application used images are taken by 4 different phases called pre-contrasted, arterial, portal venous, and delay venous from 30 patient. Images registered with efficient subpixel registration by cross correlation method. Discrete wavelet transform(DWT) based image fusion algorithm used and maximum selection method applied as fusion rule. As result 180 fused images obtained The performances of fusion results compared with structural similarity index (SSIM), peak to noise ratio (PSNR) and fusion factor (FF) metrics. In the fusion of portal venous phase and delay venous phase images, 98.7% SSIM and 74.95 dB PSNR values were obtained, respectively. FF value in the fusion of pre-contrast phase & arterial phase images measured as 7.258. In comparison of lesion types were represented with 98.5% SSIM
Year
Venue
Keywords
2017
Signal Processing and Communications Applications Conference
image fusion,liver MR imaging,wavelet transform
Field
DocType
ISSN
Computer vision,Image fusion,Computer science,Fusion,Focal nodular hyperplasia,Discrete wavelet transform,Artificial intelligence,Subpixel rendering,Wavelet transform,Wavelet,Magnetic resonance imaging
Conference
2165-0608
Citations 
PageRank 
References 
0
0.34
3
Authors
2
Name
Order
Citations
PageRank
Saim Ervural100.68
Murat Ceylan2808.37