2016 JRNL PP Christian Lutzweiler - 1.pdf
Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
Terbatas  Irwan Sofiyan
» Gedung UPT Perpustakaan
The concept of sparsity is extensively exploited in
the fields of data acquisition and image processing, contributing
to better signal-to-noise and spatio-temporal performance of the
various imaging methods. In the field of optoacoustic tomography,
the image reconstruction problem is often characterized
by computationally extensive inversion of very large datasets, for
instance when acquiring volumetric multispectral data with high
temporal resolution. In this article we seek to accelerate accurate
model-based optoacoustic inversions by identifying various
sources of sparsity in the forward and inverse models as well as
in the single- and multi-frame representation of the projection
data. These sources of sparsity are revealed through appropriate
transformations in the signal, model and image domains and are
subsequently exploited for expediting image reconstruction. The
sparsity-based inversion scheme was tested with experimental
data, offering reconstruction speed enhancement by a factor
of 40 to 700 times as compared with the conventional iterative
model-based inversions while preserving similar image quality.
The demonstrated results pave the way for achieving real-time
performance of model-based reconstruction in multi-dimensional
optoacoustic imaging.