Share Email Print
cover

Journal of Electronic Imaging

Merging of orthogonally sampled projection sets as a means for eliminating correlation artifacts from tomograms
Author(s): Richard L. Webber; Alexander L. Berestov; Jeffrey W. Duryea; Fredrick H Fahey
Format Member Price Non-Member Price
PDF $20.00 $25.00

Paper Abstract

We explore the feasibility of merging independent data sets to mitigate volume anisotropy intrinsic to tomosynthetic reconstructions. Two independent sets of orthogonally oriented projection data are obtained, respectively, from a hand phantom and from frozen breast tissues. Both objects are enclosed within radiolucent containers containing multiple fiducial reference objects. The latter facilitates registration of multiple projections produced by incrementally moving the x-ray source relative to the object about a single axis through a fixed series of angles. These data encompass maximum angular disparities up to 90 deg for each projection series. The resulting data are projectively transformed and nonlinearly processed using tuned-aperture computed tomography to yield a number of contiguous slices equal to the linear resolution of the sampled projections measured in pixels. The resulting slice data are then corrected for differential magnification, appropriately rotated, and linearly merged to yield a relatively complete, volumetrically isotropic representation of the phantom that could be visualized from any desired angle with negligible apparent tomosynthetic distortion. The resulting displays are evaluated subjectively and compared quantitatively with control images produced from optimum projection geometries. The results are consistent with the hypothesis that volume anisotropy intrinsic to tomosynthetic reconstructions can be minimized through integration of contiguously sampled orthogonal projections.

Paper Details

Date Published: 1 January 2003
PDF: 6 pages
J. Electron. Imaging. 12(1) doi: 10.1117/1.1526848
Published in: Journal of Electronic Imaging Volume 12, Issue 1
Show Author Affiliations
Richard L. Webber, Wake Forest Univ. School of Medicine (United States)
Alexander L. Berestov, Canon USA Inc. (United States)
Jeffrey W. Duryea, Brigham & Women's Hospital (United States)
Fredrick H Fahey, Wake Forest Univ. School of Medicine (United States)


© SPIE. Terms of Use
Back to Top