Successive binary algebraic reconstruction technique: An algorithm
for reconstruction from limited angle and limited number of projections
decomposed into individual components
Affiliations: Department of Electrical and Computer Engineering,
Johns Hopkins University, Baltimore, MD, USA | Division of Medical Imaging Physics, The Russell H.
Morgan Department of Radiology and Radiological Science, Johns Hopkins
University, Baltimore, MD, USA | Quantum Medical Metrics, LLC, Baltimore, MD, USA
Note: [] Corresponding author: Alia S. Khaled, Department of Electrical
and Computer Engineering, Johns Hopkins University, 3400 N. Charles St, Barton
105, Baltimore, MD 21218, USA. Tel.: +1 443 763 6791; E-mail: akhaled@jhu.edu
Abstract: Relatively high radiation CT techniques are being widely used in
diagnostic imaging raising the concerns about cancer risk especially for
routine screening of asymptomatic populations. An important strategy for dose
reduction is to reduce the number of projections, although doing so with high
image quality is technically difficult. We developed an algorithm to
reconstruct discrete (limited gray scale) images decomposed into individual
tissue types from a small number of projections acquired over a limited view
angle. The algorithm was tested using projection simulations from segmented CT
scans of different cross sections including mid femur, distal femur and lower
leg. It can provide high quality images from as low as 5–7 projections if the
skin boundary of the cross section is used as prior information in the
reconstruction process, and from 11–13 projections if the skin boundary is unknown.
