Feasibility of half-data image reconstruction in 3-D reflectivity tomography with a spherical aperture

Mark A. Anastasio, Jin Zhang, Emil Y. Sidky, Yu Zou, Dan Xia, Xiaochuan Pan

Research output: Contribution to journalArticle

Abstract

Reflectivity tomography is an imaging technique that seeks to reconstruct certain acoustic properties of a weakly scattering object. Besides being applicable to pure ultrasound imaging techniques, the reconstruction theory of reflectivity tomography is also pertinent to hybrid imaging techniques such as thermoacoustic tomography. In this work, assuming spherical scanning apertures, redundancies in the three-dimensional (3-D) reflectivity tomography data function are identified and formulated mathematically. These data redundancies are used to demonstrate that knowledge of the measured data function over half of its domain uniquely specifies the 3-D object function. This indicates that, in principle, exact image reconstruction can be performed using a "half-scan" data function, which corresponds to temporally untruncated measurements acquired on a hemi-spherical aperture, or using a "half-time" data function, which corresponds to temporally truncated measurements acquired on the entire spherical aperture. Both of these minimal scanning configurations have important biological imaging applications. An iterative reconstruction method is utilized for reconstruction of a simulated 3-D object from noiseless and noisy half-scan and half-time data functions.

Original languageEnglish (US)
Pages (from-to)1110-1112
Number of pages3
JournalIEEE Transactions on Medical Imaging
Volume24
Issue number9
DOIs
StatePublished - Sep 1 2005
Externally publishedYes

Keywords

  • Image reconstruction
  • Photoacoustic tomography
  • Refectivity tomography
  • Spherical Radon transform
  • Thermoacoustic tomography

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computational Theory and Mathematics

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