Iterative photoacoustic image reconstruction for three-dimensional imaging by conventional linear-array detection with sparsity regularization

2017 ◽  
Author(s):  
Hamid Moradi ◽  
Mohammad Honarvar ◽  
Shuo Tang ◽  
Septimiu E. Salcudean
Keyword(s):  
Image Reconstruction ◽  
Linear Array ◽  
Three Dimensional ◽  
Three Dimensional Imaging ◽  
Sparsity Regularization ◽  
Array Detection

Three-dimensional photoacoustic imaging by sparse-array detection and iterative image reconstruction

2008 ◽  
Vol 13 (5) ◽  
pp. 054052 ◽  
Author(s):  
Pinhas Ephrat ◽  
Lynn Keenliside ◽  
Adam Seabrook ◽  
Frank S. Prato ◽  
Jeffrey J. L. Carson
Keyword(s):  
Image Reconstruction ◽  
Photoacoustic Imaging ◽  
Three Dimensional ◽  
Iterative Image Reconstruction ◽  
Sparse Array ◽  
Array Detection

scholarly journals Coherent-weighted three-dimensional image reconstruction in linear-array-based photoacoustic tomography

2016 ◽  
Vol 7 (5) ◽  
pp. 1957 ◽  
Author(s):  
Depeng Wang ◽  
Yuehang Wang ◽  
Yang Zhou ◽  
Jonathan F. Lovell ◽  
Jun Xia
Keyword(s):  
Image Reconstruction ◽  
Linear Array ◽  
Three Dimensional ◽  
Photoacoustic Tomography ◽  
Dimensional Image

Criteria and Methods for Reliable Three-Dimensional Image Reconstruction

1974 ◽  
Vol 32 ◽  
pp. 330-331
Author(s):  
R. A. Crowther
Keyword(s):  
Image Reconstruction ◽  
Finite Number ◽  
Density Distribution ◽  
Electron Micrographs ◽  
Mathematical Problem ◽  
Three Dimensional ◽  
Ideal Case ◽  
Dimensional Image ◽  
General Object ◽  
The Ideal

The reconstruction of a three-dimensional image of a specimen from a set of electron micrographs reduces, under certain assumptions about the imaging process in the microscope, to the mathematical problem of reconstructing a density distribution from a set of its plane projections.In the absence of noise we can formulate a purely geometrical criterion, which, for a general object, fixes the resolution attainable from a given finite number of views in terms of the size of the object. For simplicity we take the ideal case of projections collected by a series of m equally spaced tilts about a single axis.

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