Data redundancy and reduced-scan reconstruction in reflectivity tomography

In reflectivity tomography, conventional reconstruction approaches require that measurements be acquired at view angles that span a full angular range of 2/spl pi/. It is often, however, advantageous to reduce the angular range over which measurements are acquired, in order, for example, to minimize...

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Bibliographic Details
Published in:IEEE transactions on image processing 2003-07, Vol.12 (7), p.784-795
Main Authors: Xiaochuan Pan, Yu Zou, Anastasio, M.A.
Format: Article
Language:English
Subjects:
Acoustic measurements
Applied sciences
Biomedical imaging
Biomedical measurements
Boundaries
Computed tomography
Exact sciences and technology
Image processing
Image reconstruction
Information, signal and communications theory
Ionizing radiation
Mathematical analysis
Mathematical models
Movements
Pulse measurements
Reconstruction
Reflectivity
Signal processing
Telecommunications and information theory
Tomography
Ultrasonic imaging
Ultrasonic variables measurement
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Summary:In reflectivity tomography, conventional reconstruction approaches require that measurements be acquired at view angles that span a full angular range of 2/spl pi/. It is often, however, advantageous to reduce the angular range over which measurements are acquired, in order, for example, to minimize artifacts due to movements of the imaged object. Moreover, in certain situations, it may not be experimentally possible to collect data over a 2/spl pi/ angular range. We investigate the problem of reconstructing images from reduced-scan data in reflectivity tomography. By exploiting symmetries in the data function of reflectivity tomography, we demonstrate heuristically that an image function can be uniquely specified by reduced-scan data that correspond to measurements taken over an angular interval (possibly disjoint) that spans at least /spl pi/ radians. We also identify sufficient conditions that permit for a stable reconstruction of image boundaries from reduced-scan data. Numerical results in computer-simulation studies indicate that images can be reconstructed accurately from reduced-scan data.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2003.814244