NDLI: Optimization of estimator performance and comparison to human classification performance as applied to thoracic Ga-67 SPECT images

Content Provider	IEEE Xplore Digital Library
Author	Wells, R.G. Gifford, H.C. King, M.A.
Copyright Year	2000
Description	Author affiliation: Dept. of Nucl. Med., Massachusetts Univ. Med. Center, Worcester, MA, USA (Wells, R.G.)
Abstract	Quantitative SPECT is believed to have the potential to both improve and expand upon the current diagnostic capabilities of SPECT. The benefits of quantitation will depend, however, on the accuracy and reliability of the estimator. The authors have previously evaluated the choice of estimator for the task of determining the activity of a detected tumor within a transverse slice of a thoracic Ga-67 SPECT scan. Here, the authors examine estimator performance for this same task over a range of reconstruction protocols. Reconstruction is by filtered backprojection with Chang attenuation correction and 2D or 3D Butterworth postfiltering using filter cut-offs from 0.025 cycles/pixel to no cut-off. Two estimators are considered which differ in that the region of interest (ROI) boundaries are determined from the original tumor geometry in one and by edge-detection in the other. Estimator performance is evaluated based on a measure which equally weights bias squared and variance. Calculation of the measure is based upon 35 clinically relevant locations and 200 noise realizations per location. Comparison is made to human-observer lesion-detection performance as evaluated with a localization ROC experiment with similar images. Results indicate that there is an optimal choice of filter cut-off for the estimation task which differs from that for classification. 2D and 3D post-filtering result in equivalent optimal estimator performance, contrary to what has been seen for classification performance. In conclusion, optimal estimation depends upon the reconstruction protocol and the dependence is markedly different than that for classification.
Starting Page	480
Ending Page	483
File Size	438377
Page Count	4
File Format	PDF
ISBN	0780364651
ISSN	1094687X
DOI	10.1109/IEMBS.2000.900780
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-07-23
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image reconstruction Protocols Lesions Neoplasms Attenuation Humans Low pass filters Filtering Diseases X-ray imaging
Content Type	Text
Resource Type	Article

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