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Proceedings Paper

Optical image reconstruction using DC data: enhanced experimental results with tissue-like phantoms
Author(s): Huabei Jiang; Keith D. Paulsen; Ulf L. Oesterberg
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Paper Abstract

An experimental study of detectability in steady-state optical image reconstruction through varying the single target size (15 mm - 4 mm in diameters) at three different locations (center, middle and near boundary surface) and a through evaluation of our finite element based image reconstruction algorithm to distinguish multiple targets are performed in this paper. The multi-target experiments consisted of several interested geometric and contrast combinations including two targets with the same contrast (2:1 between the target and the background) at three different separation distances, two targets with different contrasts (2:1 and 4:1) at two different separation distances and three targets with the same and different sizes (20 mm, 15 mm and 8 mm in diameters) and contrasts (2:1, 4:1 and 8:1) respectively. The reconstruction algorithm used along with a few imaging enhancement methods including total variation minimization, dual meshing and spatial low pass filtering are discussed. Quantitative measures of image quality including the size, location and shape of the heterogeneity are used to quantify the analysis. The results show that near 22:1 ratio (tissue thickness relative to detectable anomaly size) can be obtained and multiple targets can be correctly resolved using dc data with an 86 mm diameter circular tissue-like phantom.

Paper Details

Date Published: 18 August 1997
PDF: 9 pages
Proc. SPIE 2979, Optical Tomography and Spectroscopy of Tissue: Theory, Instrumentation, Model, and Human Studies II, (18 August 1997); doi: 10.1117/12.280244
Show Author Affiliations
Huabei Jiang, Purdue Univ. (United States)
Keith D. Paulsen, Dartmouth College (United States)
Ulf L. Oesterberg, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 2979:
Optical Tomography and Spectroscopy of Tissue: Theory, Instrumentation, Model, and Human Studies II
Britton Chance; Robert R. Alfano, Editor(s)

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