报告名称:

Nonconvex Total Variation-Based MRI Rician Denoising Model with Spatially Adaptive Regularization Parameters

报告作者：

刘文

作者简介：

所在学校：

武汉理工大学

职称：

副教授

其他

报告时间：

2015年12月31日下午4：30

报告地点：

威廉希尔201

报告摘要：

The purpose of this study is to enhance the quality of Magnetic resonance image (MRI) using feature-preserving denoising method. A non-convex total variation-based MRI denoising model is proposed based on global hyper-Laplacian prior and Rician noise assumption. The proposed method takes full advantage of the global MR image prior and local image features. The experimental results have demonstrated the superior performance of the proposed model in terms of quantitative and qualitative image quality evaluations.