Simultaneous Coordinate Maximization Algorithm for Maximum A Posteriori Compton Camera Imaging With Markov Random Field Prior

It is widely acknowledged that maximum a posteriori (MAP) estimation, when combined with a Markov random field (MRF) prior, is an effective tool for Compton camera imaging from Poisson data. While MAP estimation involves solving an optimization problem, the primary challenge arises from the correlat...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on instrumentation and measurement Ročník 74; s. 1 - 17
Hlavní autoři:	Le, Nhan, Snoussi, Hichem, Iltis, Alain
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Algorithms Cameras Comparative studies Complexity theory Compton camera imaging Convergence Correlation Estimation Fields (mathematics) Image reconstruction Imaging Markov random field (MRF) Markov random fields Maximization maximum a posteriori (MAP) estimation Numerical methods Optimization real-world data reconstruction algorithm Reconstruction algorithms simultaneous coordinate maximization (SCM)
ISSN:	0018-9456, 1557-9662
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	It is widely acknowledged that maximum a posteriori (MAP) estimation, when combined with a Markov random field (MRF) prior, is an effective tool for Compton camera imaging from Poisson data. While MAP estimation involves solving an optimization problem, the primary challenge arises from the correlation inherent in the MRF prior. Unlike most existing expectation maximization (EM)-like algorithms that address this challenge indirectly, we propose a simultaneous coordinate maximization (SCM) algorithm to directly handle convex MRF priors. Basically, the proposed algorithm breaks the correlation within MRF in the same way as sequential coordinate ascent (CA) algorithms; however, it allows updating all coordinates simultaneously at each iteration, rather than one coordinate or one block of coordinates sequentially. It is thus applicable to large-scale optimization problems, and hence especially suitable for high-dimensional Compton image reconstruction in real time. We prove the convergence of the SCM algorithm and analyze its convergence rate and complexity using both analytical and numerical methods. In light of the SCM algorithm, we develop a closed-form algorithm called MAP-SCM-EM for Compton camera imaging under the assumption of the EM surrogate of the Poisson log-likelihood function and the zero-mean Gaussian MRF prior. Numerous comparative studies with more classical reconstruction algorithms using real-world data, conducted with hand-held CeBr 3 Temporal Compton cameras developed by Damavan company, have confirmed that our algorithm offers a good compromise between speed and accuracy of reconstruction.
AbstractList	It is widely acknowledged that maximum a posteriori (MAP) estimation, when combined with a Markov random field (MRF) prior, is an effective tool for Compton camera imaging from Poisson data. While MAP estimation involves solving an optimization problem, the primary challenge arises from the correlation inherent in the MRF prior. Unlike most existing expectation maximization (EM)-like algorithms that address this challenge indirectly, we propose a simultaneous coordinate maximization (SCM) algorithm to directly handle convex MRF priors. Basically, the proposed algorithm breaks the correlation within MRF in the same way as sequential coordinate ascent (CA) algorithms; however, it allows updating all coordinates simultaneously at each iteration, rather than one coordinate or one block of coordinates sequentially. It is thus applicable to large-scale optimization problems, and hence especially suitable for high-dimensional Compton image reconstruction in real time. We prove the convergence of the SCM algorithm and analyze its convergence rate and complexity using both analytical and numerical methods. In light of the SCM algorithm, we develop a closed-form algorithm called MAP-SCM-EM for Compton camera imaging under the assumption of the EM surrogate of the Poisson log-likelihood function and the zero-mean Gaussian MRF prior. Numerous comparative studies with more classical reconstruction algorithms using real-world data, conducted with hand-held CeBr3 Temporal Compton cameras developed by Damavan company, have confirmed that our algorithm offers a good compromise between speed and accuracy of reconstruction. It is widely acknowledged that maximum a posteriori (MAP) estimation, when combined with a Markov random field (MRF) prior, is an effective tool for Compton camera imaging from Poisson data. While MAP estimation involves solving an optimization problem, the primary challenge arises from the correlation inherent in the MRF prior. Unlike most existing expectation maximization (EM)-like algorithms that address this challenge indirectly, we propose a simultaneous coordinate maximization (SCM) algorithm to directly handle convex MRF priors. Basically, the proposed algorithm breaks the correlation within MRF in the same way as sequential coordinate ascent (CA) algorithms; however, it allows updating all coordinates simultaneously at each iteration, rather than one coordinate or one block of coordinates sequentially. It is thus applicable to large-scale optimization problems, and hence especially suitable for high-dimensional Compton image reconstruction in real time. We prove the convergence of the SCM algorithm and analyze its convergence rate and complexity using both analytical and numerical methods. In light of the SCM algorithm, we develop a closed-form algorithm called MAP-SCM-EM for Compton camera imaging under the assumption of the EM surrogate of the Poisson log-likelihood function and the zero-mean Gaussian MRF prior. Numerous comparative studies with more classical reconstruction algorithms using real-world data, conducted with hand-held CeBr 3 Temporal Compton cameras developed by Damavan company, have confirmed that our algorithm offers a good compromise between speed and accuracy of reconstruction.
Author	Snoussi, Hichem Iltis, Alain Le, Nhan
Author_xml	– sequence: 1 givenname: Nhan orcidid: 0000-0003-3873-2795 surname: Le fullname: Le, Nhan email: thi-ai-nhan.le@utt.fr organization: Computer Science and Digital Society Laboratory, Troyes University of Technology, Troyes, France – sequence: 2 givenname: Hichem orcidid: 0000-0002-6563-2135 surname: Snoussi fullname: Snoussi, Hichem email: hichem.snoussi@utt.fr organization: Computer Science and Digital Society Laboratory, Troyes University of Technology, Troyes, France – sequence: 3 givenname: Alain orcidid: 0000-0002-3443-5390 surname: Iltis fullname: Iltis, Alain email: alain.iltis@damavan-imaging.com organization: Damavan Imaging, Troyes, France
BookMark	eNpFkEFLwzAUgINMcJvePXgIeO58SZukOY7hdLCh6MRjydbXmbk0M21FBf-7LRt4eof3fe_BNyC90pdIyCWDEWOgb5azxYgDF6NYSB0LdkL6TAgVaSl5j_QBWBrpRMgzMqiqLQAomag--X22rtnVpkTfVHTifchtaWqkC_Nlnf0xtfUlHe82Ptj6zdHCh8OqcXRMH31VY7DtrlXdvm7RiXEYDJ05s7Hlhr62ViuEd_9Jn0yZe0enFnc5fey0c3JamF2FF8c5JC_T2-XkPpo_3M0m43m05omqoxgVrmSqV-sVclOIJIfUoIaUK13olCeSr3NRSJ4ySAqJAhSg5AWoFROcs3hIrg9398F_NFjV2dY3oWxfZjFnQosEREfBgVoHX1UBi2wfrDPhO2OQdZGzNnLWRc6OkVvl6qBYRPzHGQBXgsd_N6B7AQ
CODEN	IEIMAO
Cites_doi	10.1088/0031-9155/53/12/009 10.1097/00004728-198404000-00002 10.1137/120887679 10.1109/TMI.2010.2098036 10.1109/TNS.2011.2121093 10.1088/0031-9155/61/1/243 10.1504/IJMMNO.2013.055204 10.1109/NSSMIC.2015.7582117 10.1109/TMI.2013.2265886 10.1109/42.363108 10.1016/s0003-2670(00)82860-3 10.1109/TMI.2004.831224 10.3390/s22197374 10.1109/nssmic.2018.8824429 10.1016/j.zemedi.2022.04.005 10.1109/NSSMIC.2004.1466463 10.1016/B978-012744482-6.50023-5 10.1137/1.9781611977134 10.1088/0031-9155/57/21/6779 10.1109/TRPMS.2019.2937675 10.1109/TMI.1987.4307796 10.1097/00004728-198312000-00071 10.1109/TNS.2008.2007951 10.1016/j.compbiomed.2023.107502 10.1016/j.amc.2003.08.058 10.3390/psf2023009002 10.1109/42.700734 10.1007/0-387-34946-4_1 10.1088/1361-6560/abe65f 10.1117/3.831079.ch1 10.1088/1361-6560/aac8cd 10.1109/78.193196 10.1088/0031-9155/61/8/3127 10.1088/0031-9155/51/15/R01 10.1109/TMI.2003.817767 10.1109/23.819285 10.1118/1.4959551 10.1080/17415977.2021.2011863 10.1016/0168-583X(95)80085-9 10.3109/0284186X.2011.580001 10.1109/TMI.2003.812249 10.1109/42.52985 10.1007/978-3-642-45898-9_6 10.1109/ICIP.1996.560890 10.1103/PhysRev.21.483 10.1109/TIM.2022.3165275 10.1109/42.14509 10.1109/TMI.1987.4307826 10.5109/13440 10.1109/TRPMS.2019.2929423 10.1109/83.491321 10.1016/j.net.2023.06.035 10.1109/42.563662 10.1109/78.324732 10.1118/1.3528170 10.1007/978-3-319-91578-4 10.1364/JOSAA.14.002914 10.1109/42.370409 10.1007/978-3-030-85450-8 10.1088/1361-6560/ac73d2 10.1109/42.61759 10.1109/NSSMIC.2018.8824289 10.1109/23.873014 10.1002/mp.13123 10.1051/epjconf/202328806003 10.1038/s41598-017-02377-w 10.1088/1361-6560/ab280c 10.1016/j.nima.2007.01.171 10.1109/TCI.2020.3008782 10.1016/B978-012744482-6.50024-7 10.1109/TMI.1987.4307810 10.1109/TPAMI.1984.4767596 10.1364/AO.36.008352 10.1109/NSSMIC.1998.773871 10.1007/s10107-015-0892-3 10.1109/TMI.1982.4307558 10.1137/1.9781611974997 10.1109/TIP.2010.2058811
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
DBID	97E RIA RIE AAYXX CITATION 7SP 7U5 8FD L7M
DOI	10.1109/TIM.2025.3569351
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Electronics & Communications Abstracts Solid State and Superconductivity Abstracts Technology Research Database Advanced Technologies Database with Aerospace
DatabaseTitle	CrossRef Solid State and Superconductivity Abstracts Technology Research Database Advanced Technologies Database with Aerospace Electronics & Communications Abstracts
DatabaseTitleList	Solid State and Superconductivity Abstracts
Database_xml	– sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Physics
EISSN	1557-9662
EndPage	17
ExternalDocumentID	10_1109_TIM_2025_3569351 11002752
Genre	orig-research
GrantInformation_xml	– fundername: ANR RED-7D project and BPI PIA4 Dream-Scanner project
GroupedDBID	-~X 0R~ 29I 4.4 5GY 5VS 6IK 85S 8WZ 97E A6W AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACIWK ACNCT AENEX AETIX AGQYO AGSQL AHBIQ AI. AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD F5P HZ~ H~9 IAAWW IBMZZ ICLAB IDIHD IFIPE IFJZH IPLJI JAVBF LAI M43 O9- OCL P2P RIA RIE RNS TN5 TWZ VH1 VJK AAYXX CITATION 7SP 7U5 8FD L7M
ID	FETCH-LOGICAL-c247t-3e7eb689bcbe2af54d08ae908279f982462cd5f628104f6e5070e62f07b152213
IEDL.DBID	RIE
ISICitedReferencesCount	0
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001502506800037&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0018-9456
IngestDate	Mon Jun 30 07:36:51 EDT 2025 Sat Nov 29 07:52:22 EST 2025 Wed Aug 27 01:52:23 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c247t-3e7eb689bcbe2af54d08ae908279f982462cd5f628104f6e5070e62f07b152213
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-6563-2135 0000-0003-3873-2795 0000-0002-3443-5390
PQID	3215954051
PQPubID	85462
PageCount	17
ParticipantIDs	ieee_primary_11002752 proquest_journals_3215954051 crossref_primary_10_1109_TIM_2025_3569351
PublicationCentury	2000
PublicationDate	20250000 2025-00-00 20250101
PublicationDateYYYYMMDD	2025-01-01
PublicationDate_xml	– year: 2025 text: 20250000
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	IEEE transactions on instrumentation and measurement
PublicationTitleAbbrev	TIM
PublicationYear	2025
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref57 ref12 ref56 ref15 ref59 ref14 ref58 ref53 ref52 ref11 ref55 ref10 ref54 ref17 ref16 ref19 ref18 ref51 ref50 ref46 ref45 ref48 ref47 ref42 ref41 ref44 ref43 ref49 ref8 ref7 ref9 ref4 ref3 ref6 ref5 ref40 Caffrey (ref74) 2019 ref80 ref35 ref79 ref34 ref78 ref37 ref36 ref31 ref75 ref30 ref33 ref77 ref32 ref76 ref2 ref1 ref39 ref38 ref71 ref70 ref73 ref72 Li (ref20) 2009 ref24 ref68 ref23 ref67 ref26 ref25 ref69 ref64 ref63 ref22 ref66 ref21 ref65 ref28 ref27 ref29 ref60 ref62 ref61
References_xml	– ident: ref34 doi: 10.1088/0031-9155/53/12/009 – ident: ref55 doi: 10.1097/00004728-198404000-00002 – ident: ref57 doi: 10.1137/120887679 – ident: ref42 doi: 10.1109/TMI.2010.2098036 – ident: ref59 doi: 10.1109/TNS.2011.2121093 – ident: ref66 doi: 10.1088/0031-9155/61/1/243 – ident: ref58 doi: 10.1504/IJMMNO.2013.055204 – ident: ref73 doi: 10.1109/NSSMIC.2015.7582117 – ident: ref37 doi: 10.1109/TMI.2013.2265886 – ident: ref12 doi: 10.1109/42.363108 – ident: ref60 doi: 10.1016/s0003-2670(00)82860-3 – ident: ref26 doi: 10.1109/TMI.2004.831224 – ident: ref1 doi: 10.3390/s22197374 – ident: ref50 doi: 10.1109/nssmic.2018.8824429 – ident: ref44 doi: 10.1016/j.zemedi.2022.04.005 – ident: ref31 doi: 10.1109/NSSMIC.2004.1466463 – ident: ref3 doi: 10.1016/B978-012744482-6.50023-5 – ident: ref22 doi: 10.1137/1.9781611977134 – ident: ref36 doi: 10.1088/0031-9155/57/21/6779 – ident: ref43 doi: 10.1109/TRPMS.2019.2937675 – ident: ref10 doi: 10.1109/TMI.1987.4307796 – ident: ref78 doi: 10.1097/00004728-198312000-00071 – ident: ref65 doi: 10.1109/TNS.2008.2007951 – ident: ref70 doi: 10.1016/j.compbiomed.2023.107502 – ident: ref47 doi: 10.1016/j.amc.2003.08.058 – ident: ref46 doi: 10.3390/psf2023009002 – ident: ref9 doi: 10.1109/42.700734 – year: 2019 ident: ref74 article-title: The development and evaluation of a Compton camera for imaging spent fuel rod assemblies – ident: ref75 doi: 10.1007/0-387-34946-4_1 – volume-title: Markov Random Field Modeling in Image Analysis year: 2009 ident: ref20 – ident: ref14 doi: 10.1088/1361-6560/abe65f – ident: ref28 doi: 10.1117/3.831079.ch1 – ident: ref71 doi: 10.1088/1361-6560/aac8cd – ident: ref29 doi: 10.1109/78.193196 – ident: ref77 doi: 10.1088/0031-9155/61/8/3127 – ident: ref21 doi: 10.1088/0031-9155/51/15/R01 – ident: ref72 doi: 10.1109/TMI.2003.817767 – ident: ref63 doi: 10.1109/23.819285 – ident: ref38 doi: 10.1118/1.4959551 – ident: ref53 doi: 10.1080/17415977.2021.2011863 – ident: ref2 doi: 10.1016/0168-583X(95)80085-9 – ident: ref6 doi: 10.3109/0284186X.2011.580001 – ident: ref18 doi: 10.1109/TMI.2003.812249 – ident: ref23 doi: 10.1109/42.52985 – ident: ref80 doi: 10.1007/978-3-642-45898-9_6 – ident: ref76 doi: 10.1109/ICIP.1996.560890 – ident: ref79 doi: 10.1103/PhysRev.21.483 – ident: ref32 doi: 10.1109/TIM.2022.3165275 – ident: ref11 doi: 10.1109/42.14509 – ident: ref16 doi: 10.1109/TMI.1987.4307826 – ident: ref7 doi: 10.5109/13440 – ident: ref41 doi: 10.1109/TRPMS.2019.2929423 – ident: ref27 doi: 10.1109/83.491321 – ident: ref40 doi: 10.1016/j.net.2023.06.035 – ident: ref30 doi: 10.1109/42.563662 – ident: ref13 doi: 10.1109/78.324732 – ident: ref35 doi: 10.1118/1.3528170 – ident: ref49 doi: 10.1007/978-3-319-91578-4 – ident: ref52 doi: 10.1364/JOSAA.14.002914 – ident: ref25 doi: 10.1109/42.370409 – ident: ref48 doi: 10.1007/978-3-030-85450-8 – ident: ref69 doi: 10.1088/1361-6560/ac73d2 – ident: ref24 doi: 10.1109/42.61759 – ident: ref68 doi: 10.1109/NSSMIC.2018.8824289 – ident: ref5 doi: 10.1109/23.873014 – ident: ref15 doi: 10.1002/mp.13123 – ident: ref61 doi: 10.1051/epjconf/202328806003 – ident: ref67 doi: 10.1038/s41598-017-02377-w – ident: ref39 doi: 10.1088/1361-6560/ab280c – ident: ref64 doi: 10.1016/j.nima.2007.01.171 – ident: ref62 doi: 10.1109/TCI.2020.3008782 – ident: ref4 doi: 10.1016/B978-012744482-6.50024-7 – ident: ref17 doi: 10.1109/TMI.1987.4307810 – ident: ref19 doi: 10.1109/TPAMI.1984.4767596 – ident: ref51 doi: 10.1364/AO.36.008352 – ident: ref54 doi: 10.1109/NSSMIC.1998.773871 – ident: ref45 doi: 10.1007/s10107-015-0892-3 – ident: ref8 doi: 10.1109/TMI.1982.4307558 – ident: ref56 doi: 10.1137/1.9781611974997 – ident: ref33 doi: 10.1109/TIP.2010.2058811
SSID	ssj0007647
Score	2.4255908
Snippet	It is widely acknowledged that maximum a posteriori (MAP) estimation, when combined with a Markov random field (MRF) prior, is an effective tool for Compton...
SourceID	proquest crossref ieee
SourceType	Aggregation Database Index Database Publisher
StartPage	1
SubjectTerms	Accuracy Algorithms Cameras Comparative studies Complexity theory Compton camera imaging Convergence Correlation Estimation Fields (mathematics) Image reconstruction Imaging Markov random field (MRF) Markov random fields Maximization maximum a posteriori (MAP) estimation Numerical methods Optimization real-world data reconstruction algorithm Reconstruction algorithms simultaneous coordinate maximization (SCM)
Title	Simultaneous Coordinate Maximization Algorithm for Maximum A Posteriori Compton Camera Imaging With Markov Random Field Prior
URI	https://ieeexplore.ieee.org/document/11002752 https://www.proquest.com/docview/3215954051
Volume	74
WOSCitedRecordID	wos001502506800037&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1557-9662 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0007647 issn: 0018-9456 databaseCode: RIE dateStart: 19630101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3Nb9MwFLdYBdI4DChFlHXIh104pE39EcfHqqKi0jpNUERvkRM7LNKSoDatdtn_zntOOkCIA7dIjp8i_-Ln33t-H4RcMrxZFEIG0kkeCMfDILZWB1IDf5BWcJ76OrNX6vo63mz0TZes7nNhnHM--MyN8dHf5ds626OrbILlzZiSoHFPlFJtstaj2lWRaAtkTmEHAy043kmGerJersASZHLMZaS5nP5xBvmmKn9pYn-8LF7854e9JGcdj6SzFvhX5Imr-uT5b9UF--SZj-7Mdq_Jw5cCAwdN5cDOp_MaDM6iApJJV-a-KLtMTDq7-15vi-a2pEBk26F9SWcU-_mCSBijqD2ALNK5QV8WXZa-xxH9BrMoZv3UB_rZVLYu6QIj4-gNThuQr4uP6_mnoOu7EGRMqCbgDhulxDrNUsdMLoUNY-OwN7rSuY6ZiFhmZR6xGGy5PHJAKUMXsTxUKbABNuVvSK-qK_eWUAOybMytMynAY4QODQdGpgwSn1jIIflwRCL50ZbXSLxZEuoEUEsQtaRDbUgGuPK_3usWfUhGR-ySbgPuEg5URiMbnb77x7RzcorSW3fKiPSa7d5dkKfZoSl22_f-3_oJYhPLhA
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB5VBUR74FFadaGAD71wSJv4kcTH1YpVV91dVXQRvUVO7JRIJKn2UfXCf2fGyfIQ4sAtkmMn8mePv_G8AE45WRalVIFySgTSiTBIrdWB0sgflJVC5D7P7DSZz9ObG33VB6v7WBjnnHc-c2f06G35ti02dFV2TunNeKJQ4j5SUvKoC9f6KXiTWHYpMiPcw0gMtlbJUJ8vJjPUBbk6EyrWQkV_nEK-rMpfstgfMOPn__lrL-BZzyTZsIP-Jey45gD2f8sveABPvH9nsXoF368rch00jUNNn41aVDmrBmkmm5mHqu5jMdnw2227rNZfa4ZUtmva1GzIqKIvDoltjOQH0kU2MnSbxSa1r3LEvmAvRnE_7T37ZBrb1mxMvnHsirodwufxx8XoIugrLwQFl8k6EI5KpaQ6L3LHTamkDVPjqDp6okudchnzwqoy5ilqc2XskFSGLuZlmOTIB3gkjmC3aRt3DMzgWDYV1pkc4TFSh0YgJ0sMUZ9UqgF82CKR3XUJNjKvmIQ6Q9QyQi3rURvAIc38r_f6SR_AyRa7rN-Cq0wgmdHER6PX_-j2Hp5eLGbTbDqZX76BPfpSd7lyArvr5ca9hcfF_bpaLd_5dfYDIMLOyw
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=Simultaneous+Coordinate+Maximization+Algorithm+for+Maximum+A+Posteriori+Compton+Camera+Imaging+With+Markov+Random+Field+Prior&rft.jtitle=IEEE+transactions+on+instrumentation+and+measurement&rft.au=Le%2C+Nhan&rft.au=Snoussi%2C+Hichem&rft.au=Iltis%2C+Alain&rft.date=2025&rft.pub=IEEE&rft.issn=0018-9456&rft.volume=74&rft.spage=1&rft.epage=17&rft_id=info:doi/10.1109%2FTIM.2025.3569351&rft.externalDocID=11002752
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0018-9456&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0018-9456&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0018-9456&client=summon