Authors:
Giuseppe Placidi
1
;
Luigi Cinque
2
;
Andrea Petracca
1
;
Matteo Polsinelli
1
and
Matteo Spezialetti
1
Affiliations:
1
University of L'Aquila, Italy
;
2
Sapienza University, Italy
Keyword(s):
Adaptive Acquisition Method, Sparse Sampling, Compressed Sensing, Undersampling, Sparsity, Reconstruction, Radial Directions, Projections, Non-linear Reconstruction.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Cardiovascular Imaging and Cardiography
;
Cardiovascular Technologies
;
Computer Vision, Visualization and Computer Graphics
;
Health Engineering and Technology Applications
;
Image Understanding
;
Medical Imaging
;
Pattern Recognition
;
Signal Processing
;
Software Engineering
Abstract:
Magnetic Resonance Imaging (MRI) represents a major imaging modality for its low invasiveness and for its
property to be used in real-time and functional applications. The acquisition of radial directions is often used
but a complete examination always requires long acquisition times. The only way to reduce acquisition time is
undersampling. We present an iterative adaptive acquisition method (AAM) for radial sampling/reconstruction
MRI that uses the information collected during the sequential acquisition process on the inherent structure of
the underlying image for calculating the following most informative directions. A full description of AAM is
furnished and some experimental results are reported; a comparison between AAM and weighted compressed
sensing (CS) strategy is performed on numerical data. The results demonstrate that AAM converges faster
than CS and that it has a good termination criterion for the acquisition process.