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Proceedings Paper

Objective evaluation of linear and nonlinear tomosynthetic reconstruction algorithms
Author(s): Richard L. Webber; Paul F. Hemler; John E. Lavery
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Paper Abstract

This investigation objectively tests five different tomosynthetic reconstruction methods involving three different digital sensors, each used in a different radiologic application: chest, breast, and pelvis, respectively. The common task was to simulate a specific representative projection for each application by summation of appropriately shifted tomosynthetically generated slices produced by using the five algorithms. These algorithms were, respectively, (1) conventional back projection, (2) iteratively deconvoluted back projection, (3) a nonlinear algorithm similar to back projection, except that the minimum value from all of the component projections for each pixel is computed instead of the average value, (4) a similar algorithm wherein the maximum value was computed instead of the minimum value, and (5) the same type of algorithm except that the median value was computed. Using these five algorithms, we obtained data from each sensor-tissue combination, yielding three factorially distributed series of contiguous tomosynthetic slices. The respective slice stacks then were aligned orthogonally and averaged to yield an approximation of a single orthogonal projection radiograph of the complete (unsliced) tissue thickness. Resulting images were histogram equalized, and actual projection control images were subtracted from their tomosynthetically synthesized counterparts. Standard deviations of the resulting histograms were recorded as inverse figures of merit (FOMs). Visual rankings of image differences by five human observers of a subset (breast data only) also were performed to determine whether their subjective observations correlated with homologous FOMs. Nonparametric statistical analysis of these data demonstrated significant differences (P > 0.05) between reconstruction algorithms. The nonlinear minimization reconstruction method nearly always outperformed the other methods tested. Observer rankings were similar to those measured objectively.

Paper Details

Date Published: 14 April 2000
PDF: 8 pages
Proc. SPIE 3981, Medical Imaging 2000: Image Perception and Performance, (14 April 2000); doi: 10.1117/12.383114
Show Author Affiliations
Richard L. Webber, Wake Forest Univ. School of Medicine (United States)
Paul F. Hemler, Wake Forest Univ. School of Medicine (United States)
John E. Lavery, Army Research Lab. (United States)

Published in SPIE Proceedings Vol. 3981:
Medical Imaging 2000: Image Perception and Performance
Elizabeth A. Krupinski, Editor(s)

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