DocumentCode :
1814660
Title :
Analysis of unknown-location signal detectability for regularized tomographic image reconstruction
Author :
Yendiki, Anastasia ; Fessler, Jeffrey A.
Author_Institution :
Martinos Center for Biomedical Imaging, MIT, Charlestown, MA
fYear :
2006
fDate :
6-9 April 2006
Firstpage :
279
Lastpage :
282
Abstract :
Our goal is to optimize regularized image reconstruction methods for emission tomography with respect to the task of detecting small lesions of unknown location in the reconstructed images. We consider model observers whose decisions are based on finding the maximum value of a local test statistic over all possible lesion locations. We use tail probability approximations by Adler (AAP 2000) and Siegmund and Worsley (AS 1995) to evaluate the probabilities of false alarm and detection respectively for the observers of interest. We illustrate how these analytical tools can be used to optimize regularization with respect to the performance (at low probability of false alarm operating points) of a maximum channelized non-prewhitening observer
Keywords :
image reconstruction; medical image processing; optimisation; positron emission tomography; PET; emission tomography; maximum channelized nonprewhitening observer; optimization; regularized tomographic image reconstruction; small lesion detection; tail probability approximations; unknown-location signal detectability; Image analysis; Image reconstruction; Lesions; Optimization methods; Probability; Signal analysis; Signal detection; Statistical analysis; Testing; Tomography;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-9576-X
Type :
conf
DOI :
10.1109/ISBI.2006.1624907
Filename :
1624907
Link To Document :
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