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Determination of benign and malign lesions by fusion of the different phases of liver MR

机译:肝硬化不同阶段的融合测定良性和恶性病变

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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
机译:在该研究中,将T1加权的不同阶段,动态对比增强肝脏磁共振(MR)图像与基于小波的图像融合组合以支持放射科学家的决定。二手图像已标记为6种不同的焦平病变类型,局灶性结节性增生(FNH),血管瘤,囊肿,核细胞癌(CCC),肝细胞癌(HCC)和肝转移。在应用中,使用的图像由4种不同的相,称为预对比度,动脉,门静脉,以及从30名患者延迟静脉。通过跨相关方法注册的图像以高效的子像素注册。基于离散的小波变换(DWT)的图像融合算法和融合规则应用的最大选择方法。随着结果180融合图像获得了与结构相似指数(SSIM),峰值与噪声比(PSNR)和融合因子(FF)度量相比的融合结果的性能。在门静相和延迟静脉期图像的融合中,分别获得98.7℃和74.95dB的PSNR值。在预造影相和动脉相位图像的融合中的FF值测量为7.258。相比之下,用98.5 %SSIM表示

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