A 3D MRI denoising algorithm based on Bayesian theory

详细信息    查看全文

• 作者：Fabio Baselice ; Giampaolo Ferraioli ; Vito Pascazio
• 关键词：3D MRI denoising ; Maximum a posteriori ; Markov random fields ; Statistical signal processing
• 刊名：BioMedical Engineering OnLine
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：16
• 期：1
• 全文大小：3521KB
• 刊物类别：Engineering
• 刊物主题：Biomedical Engineering; Biomaterials; Biotechnology; Biomedical Engineering/Biotechnology;
• 出版者：BioMed Central
• ISSN：1475-925X
• 卷排序：16

文摘

BackgroundWithin this manuscript a noise filtering technique for magnetic resonance image stack is presented. Magnetic resonance images are usually affected by artifacts and noise due to several reasons. Several denoising approaches have been proposed in literature, with different trade-off between computational complexity, regularization and noise reduction. Most of them is supervised, i.e. requires the set up of several parameters. A completely unsupervised approach could have a positive impact on the community.