Document Detail


List-mode likelihood.
MedLine Citation:
PMID:  9379247     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
As photon-counting imaging systems become more complex, there is a trend toward measuring more attributes of each individual event. In various imaging systems the attributes can include several position variables, time variables, and energies. If more than about four attributes are measured for each event, it is not practical to record the data in an image matrix. Instead it is more efficient to use a simple list where every attribute is stored for every event. It is the purpose of this paper to discuss the concept of likelihood for such list-mode data. We present expressions for list-mode likelihood with an arbitrary number of attributes per photon and for both preset counts and preset time. Maximization of this likelihood can lead to a practical reconstruction algorithm with list-mode data, but that aspect is covered in a separate paper [IEEE Trans. Med. Imaging (to be published)]. An expression for lesion detectability for list-mode data is also derived and compared with the corresponding expression for conventional binned data.
Authors:
H H Barrett; T White; L C Parra
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Journal of the Optical Society of America. A, Optics, image science, and vision     Volume:  14     ISSN:  1084-7529     ISO Abbreviation:  J Opt Soc Am A Opt Image Sci Vis     Publication Date:  1997 Nov 
Date Detail:
Created Date:  1997-11-10     Completed Date:  1997-11-10     Revised Date:  2012-05-07    
Medline Journal Info:
Nlm Unique ID:  9800943     Medline TA:  J Opt Soc Am A Opt Image Sci Vis     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  2914-23     Citation Subset:  IM    
Affiliation:
Department of Radiology and Optical Sciences Center, University of Arizona, Tucson, USA. barrett@radiology.arizona.edu
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MeSH Terms
Descriptor/Qualifier:
Image Processing, Computer-Assisted / methods*,  statistics & numerical data
Likelihood Functions*
Mathematics
Models, Statistical
Grant Support
ID/Acronym/Agency:
2RO1 CA52643/CA/NCI NIH HHS; R01 CA052643-10/CA/NCI NIH HHS
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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