A tailored ML-EM algorithm for reconstruction of truncated projection data using few view angles

Dedicated cardiac single photon emission computed tomography (SPECT) systems have the advantage of high speed and sensitivity at no loss, or even a gain, in resolution. The potential drawbacks of these dedicated systems are data truncation by the small field of view (FOV) and the lack of view angles...

Full description

Saved in:
Bibliographic Details
Published in:Physics in medicine & biology Vol. 58; no. 12; p. N157
Main Authors: Mao, Yanfei, Zeng, Gengsheng L
Format: Journal Article
Language:English
Published: England 21.06.2013
Subjects:
Algorithms
Heart - diagnostic imaging
Image Processing, Computer-Assisted - methods
Phantoms, Imaging
Tomography, Emission-Computed, Single-Photon - methods
ISSN:1361-6560, 1361-6560
Online Access:Get more information
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract Dedicated cardiac single photon emission computed tomography (SPECT) systems have the advantage of high speed and sensitivity at no loss, or even a gain, in resolution. The potential drawbacks of these dedicated systems are data truncation by the small field of view (FOV) and the lack of view angles. Serious artifacts, including streaks outside the FOV and distortion in the FOV, are introduced to the reconstruction when using the traditional emission data maximum-likelihood expectation-maximization (ML-EM) algorithm to reconstruct images from the truncated data with a small number of views. In this note, we propose a tailored ML-EM algorithm to suppress the artifacts caused by data truncation and insufficient angular sampling by reducing the image updating step sizes for the pixels outside the FOV. As a consequence, the convergence speed for the pixels outside the FOV is decelerated. We applied the proposed algorithm to truncated analytical data, Monte Carlo simulation data and real emission data with different numbers of views. The computer simulation results show that the tailored ML-EM algorithm outperforms the conventional ML-EM algorithm in terms of streak artifacts and distortion suppression for reconstruction from truncated projection data with a small number of views.
AbstractList Dedicated cardiac single photon emission computed tomography (SPECT) systems have the advantage of high speed and sensitivity at no loss, or even a gain, in resolution. The potential drawbacks of these dedicated systems are data truncation by the small field of view (FOV) and the lack of view angles. Serious artifacts, including streaks outside the FOV and distortion in the FOV, are introduced to the reconstruction when using the traditional emission data maximum-likelihood expectation-maximization (ML-EM) algorithm to reconstruct images from the truncated data with a small number of views. In this note, we propose a tailored ML-EM algorithm to suppress the artifacts caused by data truncation and insufficient angular sampling by reducing the image updating step sizes for the pixels outside the FOV. As a consequence, the convergence speed for the pixels outside the FOV is decelerated. We applied the proposed algorithm to truncated analytical data, Monte Carlo simulation data and real emission data with different numbers of views. The computer simulation results show that the tailored ML-EM algorithm outperforms the conventional ML-EM algorithm in terms of streak artifacts and distortion suppression for reconstruction from truncated projection data with a small number of views.
Dedicated cardiac single photon emission computed tomography (SPECT) systems have the advantage of high speed and sensitivity at no loss, or even a gain, in resolution. The potential drawbacks of these dedicated systems are data truncation by the small field of view (FOV) and the lack of view angles. Serious artifacts, including streaks outside the FOV and distortion in the FOV, are introduced to the reconstruction when using the traditional emission data maximum-likelihood expectation-maximization (ML-EM) algorithm to reconstruct images from the truncated data with a small number of views. In this note, we propose a tailored ML-EM algorithm to suppress the artifacts caused by data truncation and insufficient angular sampling by reducing the image updating step sizes for the pixels outside the FOV. As a consequence, the convergence speed for the pixels outside the FOV is decelerated. We applied the proposed algorithm to truncated analytical data, Monte Carlo simulation data and real emission data with different numbers of views. The computer simulation results show that the tailored ML-EM algorithm outperforms the conventional ML-EM algorithm in terms of streak artifacts and distortion suppression for reconstruction from truncated projection data with a small number of views.Dedicated cardiac single photon emission computed tomography (SPECT) systems have the advantage of high speed and sensitivity at no loss, or even a gain, in resolution. The potential drawbacks of these dedicated systems are data truncation by the small field of view (FOV) and the lack of view angles. Serious artifacts, including streaks outside the FOV and distortion in the FOV, are introduced to the reconstruction when using the traditional emission data maximum-likelihood expectation-maximization (ML-EM) algorithm to reconstruct images from the truncated data with a small number of views. In this note, we propose a tailored ML-EM algorithm to suppress the artifacts caused by data truncation and insufficient angular sampling by reducing the image updating step sizes for the pixels outside the FOV. As a consequence, the convergence speed for the pixels outside the FOV is decelerated. We applied the proposed algorithm to truncated analytical data, Monte Carlo simulation data and real emission data with different numbers of views. The computer simulation results show that the tailored ML-EM algorithm outperforms the conventional ML-EM algorithm in terms of streak artifacts and distortion suppression for reconstruction from truncated projection data with a small number of views.
Author Mao, Yanfei
Zeng, Gengsheng L
Author_xml – sequence: 1
  givenname: Yanfei
  surname: Mao
  fullname: Mao, Yanfei
  email: ymao@ucair.med.utah.edu
  organization: Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology, University of Utah, Salt Lake City, UT 84108, USA. ymao@ucair.med.utah.edu
– sequence: 2
  givenname: Gengsheng L
  surname: Zeng
  fullname: Zeng, Gengsheng L
BackLink https://www.ncbi.nlm.nih.gov/pubmed/23689102$$D View this record in MEDLINE/PubMed
BookMark eNpNkEtLAzEUhYNU7EP_gUiWbsbJo5lJlqXUB7S60fWYydzUKdOkJhnFf-9AK7g593D4uBzOFI2cd4DQNSV3lEiZE8JppqgQuZA5ZfkzFeUZmlBe0KwQBRn982M0jXFHCKWSzS_QmPFCKkrYBL0vcNJt5wM0eLPOVhusu60PbfrYY-sDDmC8iyn0JrXeYW_x4J3RaeAPwe_gmDc6adzH1m2xhW_81Q6i3baDeInOre4iXJ3uDL3dr16Xj9n65eFpuVhnZk54yigXddEwJkDUytKSKQ68Bk1rpmuipGZWK7CkBNHwktWKMqkMs5I2zBRGsBm6Pf4dWn32EFO1b6OBrtMOfB-rYQuhZMlJOaA3J7Sv99BUh9Dudfip_lZhv0pOZxI
CitedBy_id crossref_primary_10_1088_1361_6560_ab04de
crossref_primary_10_1088_1361_6560_ad5266
crossref_primary_10_1118_1_4938098
ContentType Journal Article
DBID CGR
CUY
CVF
ECM
EIF
NPM
7X8
DOI 10.1088/0031-9155/58/12/N157
DatabaseName Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
MEDLINE - Academic
DatabaseTitle MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
MEDLINE - Academic
DatabaseTitleList MEDLINE
MEDLINE - Academic
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: 7X8
  name: MEDLINE - Academic
  url: https://search.proquest.com/medline
  sourceTypes: Aggregation Database
DeliveryMethod no_fulltext_linktorsrc
Discipline Medicine
Biology
Physics
EISSN 1361-6560
ExternalDocumentID 23689102
Genre Journal Article
Research Support, N.I.H., Extramural
GrantInformation_xml – fundername: NHLBI NIH HHS
  grantid: 1R01HL108350
– fundername: NHLBI NIH HHS
  grantid: R01 HL108350
GroupedDBID ---
-DZ
-~X
123
1JI
4.4
5B3
5RE
5VS
5ZH
7.M
7.Q
9BW
AAGCD
AAJIO
AAJKP
AALHV
AATNI
ABCXL
ABHWH
ABJNI
ABLJU
ABQJV
ABVAM
ACAFW
ACGFS
ACHIP
AEFHF
AENEX
AERVB
AFYNE
AKPSB
ALMA_UNASSIGNED_HOLDINGS
AOAED
ASPBG
ATQHT
AVWKF
AZFZN
CBCFC
CEBXE
CGR
CJUJL
CRLBU
CS3
CUY
CVF
DU5
EBS
ECM
EDWGO
EIF
EJD
EMSAF
EPQRW
EQZZN
F5P
HAK
IHE
IJHAN
IOP
IZVLO
JCGBZ
KOT
LAP
M45
N5L
N9A
NPM
NT-
NT.
P2P
PJBAE
R4D
RIN
RNS
RO9
ROL
RPA
S3P
SY9
TN5
UCJ
W28
XPP
7X8
ADEQX
AEINN
ID FETCH-LOGICAL-c403t-135b6d225e5b9f17293e3bea1b2ab098a2fa9ef07e5d372b91289c2f81d2c6c52
IEDL.DBID 7X8
ISICitedReferencesCount 4
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000319966100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1361-6560
IngestDate Fri Sep 05 06:58:35 EDT 2025
Thu Jan 02 22:12:29 EST 2025
IsPeerReviewed true
IsScholarly true
Issue 12
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c403t-135b6d225e5b9f17293e3bea1b2ab098a2fa9ef07e5d372b91289c2f81d2c6c52
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
PMID 23689102
PQID 1365987307
PQPubID 23479
ParticipantIDs proquest_miscellaneous_1365987307
pubmed_primary_23689102
PublicationCentury 2000
PublicationDate 2013-06-21
PublicationDateYYYYMMDD 2013-06-21
PublicationDate_xml – month: 06
  year: 2013
  text: 2013-06-21
  day: 21
PublicationDecade 2010
PublicationPlace England
PublicationPlace_xml – name: England
PublicationTitle Physics in medicine & biology
PublicationTitleAlternate Phys Med Biol
PublicationYear 2013
References 16595492 - J Nucl Med. 2006 Apr;47(4):595-602
15470913 - Phys Med Biol. 2004 Sep 7;49(17):3903-23
15552416 - Phys Med Biol. 2004 Oct 7;49(19):4543-61
19722106 - Eur J Nucl Med Mol Imaging. 2010 Mar;37(3):528-36
18552149 - J Nucl Med. 2008 Jul;49(7):1080-9
18256734 - Int J Biomed Imaging. 2007;2007:63634
19688410 - J Nucl Cardiol. 2009 Nov-Dec;16(6):927-34
6608535 - J Comput Assist Tomogr. 1984 Apr;8(2):306-16
22421269 - Phys Med Biol. 2012 Apr 7;57(7):1873-87
19306766 - Cardiol Clin. 2009 May;27(2):227-36, Table of Contents
19369711 - Phys Med Biol. 2009 May 7;54(9):2791-805
20585775 - Eur J Nucl Med Mol Imaging. 2010 Oct;37(10):1887-902
18401067 - Phys Med Biol. 2008 May 7;53(9):2207-31
18238264 - IEEE Trans Med Imaging. 1982;1(2):113-22
References_xml – reference: 18256734 - Int J Biomed Imaging. 2007;2007:63634
– reference: 18238264 - IEEE Trans Med Imaging. 1982;1(2):113-22
– reference: 19722106 - Eur J Nucl Med Mol Imaging. 2010 Mar;37(3):528-36
– reference: 20585775 - Eur J Nucl Med Mol Imaging. 2010 Oct;37(10):1887-902
– reference: 18552149 - J Nucl Med. 2008 Jul;49(7):1080-9
– reference: 16595492 - J Nucl Med. 2006 Apr;47(4):595-602
– reference: 19306766 - Cardiol Clin. 2009 May;27(2):227-36, Table of Contents
– reference: 19688410 - J Nucl Cardiol. 2009 Nov-Dec;16(6):927-34
– reference: 6608535 - J Comput Assist Tomogr. 1984 Apr;8(2):306-16
– reference: 18401067 - Phys Med Biol. 2008 May 7;53(9):2207-31
– reference: 22421269 - Phys Med Biol. 2012 Apr 7;57(7):1873-87
– reference: 19369711 - Phys Med Biol. 2009 May 7;54(9):2791-805
– reference: 15470913 - Phys Med Biol. 2004 Sep 7;49(17):3903-23
– reference: 15552416 - Phys Med Biol. 2004 Oct 7;49(19):4543-61
SSID ssj0011824
Score 2.1021035
Snippet Dedicated cardiac single photon emission computed tomography (SPECT) systems have the advantage of high speed and sensitivity at no loss, or even a gain, in...
SourceID proquest
pubmed
SourceType Aggregation Database
Index Database
StartPage N157
SubjectTerms Algorithms
Heart - diagnostic imaging
Image Processing, Computer-Assisted - methods
Phantoms, Imaging
Tomography, Emission-Computed, Single-Photon - methods
Title A tailored ML-EM algorithm for reconstruction of truncated projection data using few view angles
URI https://www.ncbi.nlm.nih.gov/pubmed/23689102
https://www.proquest.com/docview/1365987307
Volume 58
WOSCitedRecordID wos000319966100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3NS8MwFA_qVLz4Mb_mFxG8hq5p0zQnGbLhYS07KOxWmzSZwmznOhX_e1_azp0EwUspSVtC-l7yex95P4RuQuMBaGCawPZiiK-pR0IJiic0l1RxJZiuDgoPeRyH47EYNQ63skmrXK6J1UKdFcr6yB2bjgX2MYjk7eyNWNYoG11tKDTWUcsDKGMVk49XUQTAzjWpbeASW2RmeXQOjD4rzMTWRndY6LjUiV3GfweZ1WYz2PvvMPfRbgMzca-WiwO0pvM22qqJJ7_aaDtqQurQWOWAqvIQPfWwTSct5jrD0ZD0I5xOJ_DtxfMrBmiLK9v5p94sLgyGe1tTFp5vHDq23eacYptOP8FGf2I7Xpzmk6kuj9DjoP9wd08aAgai_K5naeqZDDLQeM2kMAB1hKc9qVNX0lR2RZhSkwptulyzzONUCtjshKIGMDBVgWL0GG3kRa5PEabSBL6AHqmM70suMlD3zA1oBiaSELyDrpfzmYCA26hFmuvivUxWM9pBJ_VPSWZ1JY6EekEIeIee_eHtc7RDayoLQt0L1DKg3voSbaqPxUs5v6okB67xKPoG9x7LsA
linkProvider ProQuest
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+tailored+ML-EM+algorithm+for+reconstruction+of+truncated+projection+data+using+few+view+angles&rft.jtitle=Physics+in+medicine+%26+biology&rft.au=Mao%2C+Yanfei&rft.au=Zeng%2C+Gengsheng+L&rft.date=2013-06-21&rft.eissn=1361-6560&rft.volume=58&rft.issue=12&rft.spage=N157&rft_id=info:doi/10.1088%2F0031-9155%2F58%2F12%2FN157&rft_id=info%3Apmid%2F23689102&rft_id=info%3Apmid%2F23689102&rft.externalDocID=23689102
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1361-6560&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1361-6560&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1361-6560&client=summon