Spatiotemporal Imaging Exploiting Structured Sparsity
Abstract
The conducted research work has proven the feasibility of applying compressed sensing and sparse representations, a recently emerged signal processing technique, to achieve reduction of data acquisition while maintaining high image resolution, thus providing a solution to overcome the conventional limits of spatiotemporal imaging. Effects and capabilities of the method were investigated and validated through two case studies of functional MRI brain connectivity decomposition and dynamic contrast enhanced breast cancer imaging. Besides these thoroughly investigated case studies, other applications for high-resolution spatiotemporal imaging using compressed sensing could be developed. One Journal and three international conference papers were submitted during the project.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 06, 2019
- Accession Number
- AD1077270
Entities
People
- Thanh H Nguyen
Organizations
- Vietnamese-German University