Dependent nonparametric bayesian group dictionary learning for online reconstruction of dynamic MR images

详细信息    查看全文

• 作者：Dornoosh Zonoobi^bAuthor Vitae ; Shahrooz F. Roohi^a ; ^{shahrooz.faghihroohi@gmail.com}Author Vitae ; Ashraf A. Kassim^a ; ^{ashraf@nus.edu.sg}Author Vitae ; Jacob L. Jaremko^bAuthor Vitae
• 关键词：Dynamic 3D MRI ; Image reconstruction ; Dictionary learning ; Compressive sensing
• 刊名：Pattern Recognition
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：63
• 期：Complete
• 页码：518-530
• 全文大小：2452 K
• 卷排序：63

文摘

A novel dictionary learning-based algorithm for online reconstruction of dynamic MR images is proposed. The algorithm consists of both patch-based (local) and global sparsity terms. The group patching is employed to classify the patches based on their similarities. A modified dependent hierarchical beta process (dHBP) is utilized as the prior for the dictionary learning process.