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Proceedings Paper

Theoretical prediction of lung nodule measurement accuracy under different acquisition and reconstruction conditions
Author(s): Jiang Hsieh; Kelly Karau
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Paper Abstract

Utilization of computed tomography (CT) for lung cancer screening has attracted significant research interests in recent years. Images reconstructed from CT studies are used for lung nodule characterization and three-dimensional lung lesion sizing. Methodologies have been developed to automatically identify and characterize lung nodules. In this paper, we analyze the impact of acquisition and reconstruction parameters on the accuracy of quantitative lung nodule characterization. The two major data acquisition parameters that impact the accuracy of the lung nodule measurement are acquisition mode and slice aperture. Acquisition mode includes both axial and helical scans. The investigated reconstruction parameters are the reconstruction filters and field-of-view. We first develop theoretical models that predict the system response under various acquisition and reconstruction conditions. These models allow clinicians to compare results under different conditions and make appropriate acquisition and reconstruction decisions. To validate our model, extensive phantom experiments are conducted. Experiments have demonstrated that our analytical models accurately predict the performance parameters under various conditions. Our study indicates that acquisition and reconstruction parameters can significantly impact the accuracy of the nodule volume measurement. Consequently, when conducting quantitative analysis on lung nodules, especially in sequential growth studies, it is important to make appropriate adjustment and correction to maintain the desired accuracy and to ensure effective patient management.

Paper Details

Date Published: 30 April 2004
PDF: 7 pages
Proc. SPIE 5369, Medical Imaging 2004: Physiology, Function, and Structure from Medical Images, (30 April 2004); doi: 10.1117/12.533542
Show Author Affiliations
Jiang Hsieh, GE Medical Systems (United States)
Kelly Karau, GE Medical Systems (United States)

Published in SPIE Proceedings Vol. 5369:
Medical Imaging 2004: Physiology, Function, and Structure from Medical Images
Amir A. Amini; Armando Manduca, Editor(s)

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