CNN denoising for medical image based on wavelet domain

被引：8

作者：

Li, Lanjuan ^{[1
]}

Wu, Jingyang ^{[1
]}

Jin, Xinyu ^{[1
]}

机构：

[1] Zhejiang Univ, Coll Informat Sci & Elect Engn, Hangzhou, Zhejiang, Peoples R China

来源：

2018 NINTH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY IN MEDICINE AND EDUCATION (ITME 2018) | 2018年

关键词：

medical image; denoising; wavelet transform; convolutional neural network;

D O I：

10.1109/ITME.2018.00033

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Image denoising is one of the most important directions in image processing. Medical images are often affected by noise and interference from the environment and equipment during acquisition, conversion, and transmission, resulting in degradation. This paper mainly introduces a new convolutional neural network structure for medical image denoising-deep neural network based on wavelet domain (deep wavelet denoising net, DWDN). Our DWDN model exhibits high effectiveness in general medical image denoising tasks and is more excellent in the details of image.

引用

页码：105 / 109

页数：5

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