Optimal energy window selection for scintigraphy & emission computed tomography

Radioisotope imaging methods such as PET, SPECT and planar scintigraphy, currently utilize a fixed energy (pulse height) acceptance window regardless of the volume of the subject being imaged. This is despite previous work suggesting that higher window settings may yield improved image quality for i...

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Main Authors: Wells, Kevin, Tumian, Afidalina, Zapros, Angelos, Alnafea, Mohammed, Saripan, M. Iqbal, Guy, Matthew, Hinton , Paul
Format: Conference or Workshop Item
Language:English
Published: 2005
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Online Access:http://irep.iium.edu.my/40421/1/wells2005.pdf
http://irep.iium.edu.my/40421/
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1596736
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
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spelling my.iium.irep.404212015-01-26T09:07:12Z http://irep.iium.edu.my/40421/ Optimal energy window selection for scintigraphy & emission computed tomography Wells, Kevin Tumian, Afidalina Zapros, Angelos Alnafea, Mohammed Saripan, M. Iqbal Guy, Matthew Hinton , Paul Q Science (General) Radioisotope imaging methods such as PET, SPECT and planar scintigraphy, currently utilize a fixed energy (pulse height) acceptance window regardless of the volume of the subject being imaged. This is despite previous work suggesting that higher window settings may yield improved image quality for imaging larger objects. However, we speculate that non-standard energy windows have not been widely adopted because there has not, until now, been a method available for determining how and when to use such an approach. In this new work we address this issue and propose a method for setting an adaptive photopeak acceptance window. This should be optimal for a wide variety of imaging situations applied across different radioisotope imaging methods. In order to develop an automatic technique in which individual patient-specific optimal thresholds can be determined, we propose a Bayes’ Minimum Error Thresholding approach, which utilizes modeling the upper part of the observed energy spectrum as a two-class Gaussian mixture model. Exemplar planar Monte Carlo results and a preliminary phantom study are presented. 2005 Conference or Workshop Item REM application/pdf en http://irep.iium.edu.my/40421/1/wells2005.pdf Wells, Kevin and Tumian, Afidalina and Zapros, Angelos and Alnafea, Mohammed and Saripan, M. Iqbal and Guy, Matthew and Hinton , Paul (2005) Optimal energy window selection for scintigraphy & emission computed tomography. In: 2005 IEEE Nuclear Science Symposium Conference Record , 23rd - 29th October 2005, Fajardo. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1596736
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
Wells, Kevin
Tumian, Afidalina
Zapros, Angelos
Alnafea, Mohammed
Saripan, M. Iqbal
Guy, Matthew
Hinton , Paul
Optimal energy window selection for scintigraphy & emission computed tomography
description Radioisotope imaging methods such as PET, SPECT and planar scintigraphy, currently utilize a fixed energy (pulse height) acceptance window regardless of the volume of the subject being imaged. This is despite previous work suggesting that higher window settings may yield improved image quality for imaging larger objects. However, we speculate that non-standard energy windows have not been widely adopted because there has not, until now, been a method available for determining how and when to use such an approach. In this new work we address this issue and propose a method for setting an adaptive photopeak acceptance window. This should be optimal for a wide variety of imaging situations applied across different radioisotope imaging methods. In order to develop an automatic technique in which individual patient-specific optimal thresholds can be determined, we propose a Bayes’ Minimum Error Thresholding approach, which utilizes modeling the upper part of the observed energy spectrum as a two-class Gaussian mixture model. Exemplar planar Monte Carlo results and a preliminary phantom study are presented.
format Conference or Workshop Item
author Wells, Kevin
Tumian, Afidalina
Zapros, Angelos
Alnafea, Mohammed
Saripan, M. Iqbal
Guy, Matthew
Hinton , Paul
author_facet Wells, Kevin
Tumian, Afidalina
Zapros, Angelos
Alnafea, Mohammed
Saripan, M. Iqbal
Guy, Matthew
Hinton , Paul
author_sort Wells, Kevin
title Optimal energy window selection for scintigraphy & emission computed tomography
title_short Optimal energy window selection for scintigraphy & emission computed tomography
title_full Optimal energy window selection for scintigraphy & emission computed tomography
title_fullStr Optimal energy window selection for scintigraphy & emission computed tomography
title_full_unstemmed Optimal energy window selection for scintigraphy & emission computed tomography
title_sort optimal energy window selection for scintigraphy & emission computed tomography
publishDate 2005
url http://irep.iium.edu.my/40421/1/wells2005.pdf
http://irep.iium.edu.my/40421/
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1596736
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