Share Email Print
cover

Proceedings Paper

Novel method for automated determination of the cancellation parameter in dual-energy imaging: evaluation using anthropomorphic phantom images
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Dual-energy imaging shows increased conspicuity and specificity of lung nodule detection through the removal of undesired contrast resulting from overlying bone structures. We have developed an algorithm that automatically determines the optimal cancellation parameters for a log-subtraction technique for a pair of high- and low-energy images. The core algorithm involves shrinking the data, extracting bone features, extracting salient edge from these bone features, calculating a tissue-cancellation map, computing the maximum-likelihood bone contrast cancellation parameter, and finally, calculating the soft-tissue cancellation parameter using an empirical relationship. We verified the performance of the algorithm using observer studies, in which the value of the tissue-cancellation parameter calculated by the algorithm was compared to the value manually selected by nineteen trained observers. A number of dual-energy images were acquired with a modified GE Revolution XQ/i, flat-panel-detector chest imaging system, using an anthropomorphic phantom. The effects of variables such as patient size, kVp, mAs, lung texture, patient motion, and the presence of foreign objects in field-of-view on algorithmic performance were evaluated. We found that the algorithm-selected parameter values had less variability than those selected by the observers. Furthermore, the algorithm-selected parameter was within the limits of the variability of the observers for all cases.

Paper Details

Date Published: 5 June 2003
PDF: 11 pages
Proc. SPIE 5030, Medical Imaging 2003: Physics of Medical Imaging, (5 June 2003); doi: 10.1117/12.480195
Show Author Affiliations
John M. Sabol, GE Medical Systems (United States)
Gopal B. Avinash, GE Medical Systems (United States)


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

© SPIE. Terms of Use
Back to Top