文献类型： 会议论文
第一作者： Arnaud Ogier
作者： Arnaud Ogier 1 ; Pierre Hellier; Christian Barillot; SPIE-The International Society for Optical Engineering;
作者机构： 1.Unit/Project Visages U746, INSERM-INRIA-CNRS-Univ-Rennes1, Campus de Beaulieu, 35042 Rennes Cedex, France
关键词： denoising;wavelets;total variation;restoration;ultrasound
会议名称： Medical imaging 2006.
主办单位：
页码： 61441E.1-61441E.9
摘要： The multiplicity of sensors used in medical imaging leads to different noises. Non informative noise can damage the image interpretation process and the performance of automatic analysis. The method proposed in this paper allows compensating highly noisy image data from non informative noise without sophisticated modeling of the noise statistics. This generic approach uses jointly a wavelet decomposition scheme and a non-isotropic Total Variation filtering of the transform coefficients. This framework benefits from both the hierarchical capabilities of the wavelet transform and the well-posed regularization scheme of the Total Variation. This algorithm has been tested and validated on test-bed data, as well as different clinical MR and 3D ultrasound images, enhancing the capabilities of the proposed method to cope with different noise models.
分类号： [ "R312" , "R318.51"]
- 相关文献
[1]Restoration of 3D medical images with total variation scheme on wavelet domains (TVW). Arnaud Ogier,Pierre Hellier,Christian Barillot. 2006
[2]USING BILATERAL SYMMETRY TO IMPROVE NON-LOCAL MEANS DENOISING OF MR BRAIN IMAGES. Sylvain Prima,Olivier Commowick. 2013
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