skip to main content

Title: Covariance approximation for fast and accurate computation of channelized Hotelling observer statistics

We describe a method for computing linear observer statistics for maximum a posteriori (MAP) reconstructions of PET images. The method is based on a theoretical approximation for the mean and covariance of MAP reconstructions. In particular, we derive here a closed form for the channelized Hotelling observer (CHO) statistic applied to 2D MAP images. We show reasonably good correspondence between these theoretical results and Monte Carlo studies. The accuracy and low computational cost of the approximation allow us to analyze the observer performance over a wide range of operating conditions and parameter settings for the MAP reconstruction algorithm.
Authors:
; ;
Publication Date:
OSTI Identifier:
843117
Report Number(s):
LBNL--45512
R&D Project: 860538; TRN: US0504145
DOE Contract Number:
AC03-76SF00098
Resource Type:
Journal Article
Resource Relation:
Other Information: Journal Publication Date: 08/2000
Research Org:
Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US)
Sponsoring Org:
USDOE Director. Office of Science; National Cancer Institute Grants R01 CA59794 and R01 CA56655, US Department of Health and Human Services Grant P01 HL25840
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; ACCURACY; PERFORMANCE; STATISTICS Covariance Channelized Hotelling observer fast computation