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Proceedings Paper

Fast tomosynthesis for lung cancer detection using the SBDX geometry
Author(s): Rebecca Fahrig; Angel R. Pineda; Edward G. Solomon; Ann N.C. Leung; Norbert J. Pelc
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Paper Abstract

Radiology-based lung-cancer detection is a high-contrast imaging task, consisting of the detection of a small mass of tissue within much lower density lung parenchyma. This imaging task requires removal of confounding image details, fast image acquisition (< 0.1 s for pericardial region), low dose (comparable to a chest x-ray), high resolution (< 0.25 mm in-plane) and patient positioning flexibility. We present an investigation of tomosynthesis, implemented using the Scanning-Beam Digital X-ray System (SBDX), to achieve these goals. We designed an image-based computer model of tomosynthesis using a high-resolution (0.15-mm isotropic voxels), low-noise CT volume image of a lung phantom, numerically added spherical lesions and convolution-based tomographic blurring. Lesion visibility was examined as a function of half-tomographic angle for 2.5 and 4.0 mm diameter lesions. Gaussian distributed noise was added to the projected images. For lesions 2.5 mm and 4.0 mm in diameter, half-tomographic angles of at least 6° and 9° respectively were necessary before visualization of the lesions improved. The addition of noise for a dose equivalent to 1/10 that used for a standard chest radiograph did not significantly impair lesion detection. The results are promising, indicating that lung-cancer detection using a modified SBDX system is possible.

Paper Details

Date Published: 5 June 2003
PDF: 8 pages
Proc. SPIE 5030, Medical Imaging 2003: Physics of Medical Imaging, (5 June 2003); doi: 10.1117/12.480149
Show Author Affiliations
Rebecca Fahrig, Stanford Univ. (United States)
Angel R. Pineda, Stanford Univ. (United States)
Edward G. Solomon, NexRay, Inc. (United States)
Ann N.C. Leung, Stanford Univ. (United States)
Norbert J. Pelc, Stanford Univ. (United States)

Published in SPIE Proceedings Vol. 5030:
Medical Imaging 2003: Physics of Medical Imaging
Martin J. Yaffe; Larry E. Antonuk, Editor(s)

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