Menu 
VPA
Computer Vision And Pattern Analysis Laboratory Home Page  Home
People  People
Publications  Publications
Publications  Databases
Contact Information  Contact
Research
Supported Research Projects  Supported Research Projects
Research Activites  Research Activites
Research Groups
SPIS - Signal Processing and Information Systems Lab.SPIS - Signal Processing and Information Systems Lab.
Medical Vision and Analysis Group  Medical Research Activities
Biometrics Research Group  Biometrics Research Group
SPIS - Signal Processing and Information Systems Lab.MISAM - Machine Intelligence for Speech Audio and Multimedia.
Knowledge Base
  Paper Library
  VPA Lab Inventory
  Databases in VPALAB
Sparsity-Driven Sparse-Aperture Ultrasound Imaging
Authors: Müjdat Çetin, Emmanuel Bossy, Robin Cleveland, and W. Clem Karl
Published in: IEEE International Conference on Acoustics, Speech, and Signal Processing 2006
Publication year: 2006
Abstract: We propose an image formation algorithm for ultrasound
imaging based on sparsity-driven regularization functionals.
We consider data collected by synthetic transducer arrays,
with the primary motivating application being nondestructive
evaluation. Our framework involves the use of a physical
optics-based forward model of the observation process; the
formulation of an optimization problem for image formation;
and the solution of that problem through efficient numerical
algorithms. Our sparsity-driven, model-based approach
achieves the preservation of physical features while suppressing
spurious artifacts. It also provides robust reconstructions
in the case of sparse observation apertures. We demonstrate
the effectiveness of our imaging strategy on real ultrasound
data.
  download full paper
Download

Home Back