Segmentation in Ultrasonic B-Mode Images of Healthy Carotid Arteries Using Mixtures of Nakagami Distributions and Stochastic Optimization

The goal of this work is to perform a segmentation of the intimamedia thickness (IMT) of carotid arteries in view of computing various dynamical properties of that tissue, such as the elasticity distribution (elastogram). The echogenicity of a region of interest comprising the intima-media layers, t...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on medical imaging Vol. 28; no. 2; pp. 215 - 229
Main Authors Destrempes, F., Meunier, J., Giroux, M.-F., Soulez, G., Cloutier, G.
Format Journal Article
LanguageEnglish
Published United States IEEE 01.02.2009
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text
ISSN0278-0062
1558-254X
1558-254X
DOI10.1109/TMI.2008.929098

Cover

Abstract The goal of this work is to perform a segmentation of the intimamedia thickness (IMT) of carotid arteries in view of computing various dynamical properties of that tissue, such as the elasticity distribution (elastogram). The echogenicity of a region of interest comprising the intima-media layers, the lumen, and the adventitia in an ultrasonic B -mode image is modeled by a mixture of three Nakagami distributions. In a first step, we compute the maximum a posteriori estimator of the proposed model, using the expectation maximization (EM) algorithm. We then compute the optimal segmentation based on the estimated distributions as well as a statistical prior for disease-free IMT using a variant of the exploration/selection (ES) algorithm. Convergence of the ES algorithm to the optimal solution is assured asymptotically and is independent of the initial solution. In particular, our method is well suited to a semi-automatic context that requires minimal manual initialization. Tests of the proposed method on 30 sequences of ultrasonic B -mode images of presumably disease-free control subjects are reported. They suggest that the semi-automatic segmentations obtained by the proposed method are within the variability of the manual segmentations of two experts.
AbstractList The goal of this work is to perform a segmentation of the intimamedia thickness (IMT) of carotid arteries in view of computing various dynamical properties of that tissue, such as the elasticity distribution (elastogram). The echogenicity [abstract truncated by publisher].
The goal of this work is to perform a segmentation of the intimamedia thickness (IMT) of carotid arteries in view of computing various dynamical properties of that tissue, such as the elasticity distribution (elastogram). The echogenicity of a region of interest comprising the intima-media layers, the lumen, and the adventitia in an ultrasonic B-mode image is modeled by a mixture of three Nakagami distributions. In a first step, we compute the maximum a posteriori estimator of the proposed model, using the expectation maximization (EM) algorithm. We then compute the optimal segmentation based on the estimated distributions as well as a statistical prior for disease-free IMT using a variant of the exploration/selection (ES) algorithm. Convergence of the ES algorithm to the optimal solution is assured asymptotically and is independent of the initial solution. In particular, our method is well suited to a semi-automatic context that requires minimal manual initialization. Tests of the proposed method on 30 sequences of ultrasonic B-mode images of presumably disease-free control subjects are reported. They suggest that the semi-automatic segmentations obtained by the proposed method are within the variability of the manual segmentations of two experts.
The goal of this work is to perform a segmentation of the intimamedia thickness (IMT) of carotid arteries in view of computing various dynamical properties of that tissue, such as the elasticity distribution (elastogram).
The goal of this work is to perform a segmentation of the intimamedia thickness (IMT) of carotid arteries in view of computing various dynamical properties of that tissue, such as the elasticity distribution (elastogram). The echogenicity of a region of interest comprising the intima-media layers, the lumen, and the adventitia in an ultrasonic B-mode image is modeled by a mixture of three Nakagami distributions. In a first step, we compute the maximum a posteriori estimator of the proposed model, using the expectation maximization (EM) algorithm. We then compute the optimal segmentation based on the estimated distributions as well as a statistical prior for disease-free IMT using a variant of the exploration/selection (ES) algorithm. Convergence of the ES algorithm to the optimal solution is assured asymptotically and is independent of the initial solution. In particular, our method is well suited to a semi-automatic context that requires minimal manual initialization. Tests of the proposed method on 30 sequences of ultrasonic B-mode images of presumably disease-free control subjects are reported. They suggest that the semi-automatic segmentations obtained by the proposed method are within the variability of the manual segmentations of two experts.The goal of this work is to perform a segmentation of the intimamedia thickness (IMT) of carotid arteries in view of computing various dynamical properties of that tissue, such as the elasticity distribution (elastogram). The echogenicity of a region of interest comprising the intima-media layers, the lumen, and the adventitia in an ultrasonic B-mode image is modeled by a mixture of three Nakagami distributions. In a first step, we compute the maximum a posteriori estimator of the proposed model, using the expectation maximization (EM) algorithm. We then compute the optimal segmentation based on the estimated distributions as well as a statistical prior for disease-free IMT using a variant of the exploration/selection (ES) algorithm. Convergence of the ES algorithm to the optimal solution is assured asymptotically and is independent of the initial solution. In particular, our method is well suited to a semi-automatic context that requires minimal manual initialization. Tests of the proposed method on 30 sequences of ultrasonic B-mode images of presumably disease-free control subjects are reported. They suggest that the semi-automatic segmentations obtained by the proposed method are within the variability of the manual segmentations of two experts.
Author Destrempes, F.
Giroux, M.-F.
Soulez, G.
Meunier, J.
Cloutier, G.
Author_xml – sequence: 1
  givenname: F.
  surname: Destrempes
  fullname: Destrempes, F.
  organization: Lab. de Biorheologie et d'Ultrasonographie Medicale (LBUM), Centre de Rech. du Centre Hospitalier de I'Univ. de Montreal (CRCHUM), Montreal, QC
– sequence: 2
  givenname: J.
  surname: Meunier
  fullname: Meunier, J.
  organization: Dept. d'Inf. et de Rech. Operationnelle (DIRO), Univ. de Montreal, Montreal, QC
– sequence: 3
  givenname: M.-F.
  surname: Giroux
  fullname: Giroux, M.-F.
  organization: Dept. de Radiologie, Centre Hospitalier de I'Univ. de Montreal (CHUM), Montreal, QC
– sequence: 4
  givenname: G.
  surname: Soulez
  fullname: Soulez, G.
  organization: Dept. de Radiologie, Centre Hospitalier de I'Univ. de Montreal (CHUM), Montreal, QC
– sequence: 5
  givenname: G.
  surname: Cloutier
  fullname: Cloutier, G.
  organization: Lab. de Biorheologie et d'Ultrasonographie Medicale (LBUM), Centre de Rech. du Centre Hospitalier de I'Univ. de Montreal (CRCHUM), Montreal, QC
BackLink https://www.ncbi.nlm.nih.gov/pubmed/19068423$$D View this record in MEDLINE/PubMed
BookMark eNqFkk9PFDEYxhsDkQU9ezAxjQc9zdLOTP_MEVeRTVg5wCbemu703aU40y5tJxG_gd-aLoMcSNRLm7S_53nbPM8h2nPeAUJvKJlSSprjq8V8WhIip03ZkEa-QBPKmCxKVn_fQxNSClkQwssDdBjjDSG0ZqR5iQ5oQ7isy2qCfl_CpgeXdLLeYevwsktBR-9siz8VC28Az3u9gYj9Gp-B7tL1HZ7p4JM1-CQkCDbfLaN1G7ywP9MQRvSb_qE3urf4s40p2NWw849YO4Mvk2-vdUx5wsU22d7-ehj-Cu2vdRfh9eN-hJanX65mZ8X5xdf57OS8aGvCUkGloK0RFSNlSZiRfLUCVoGWWoBoWU1LDSafVZWEtWko4VXDGRhdUmAGRHWEPo6-2-BvB4hJ9Ta20HXagR-iklyIqmaCZPLDP0nOpaScyf-C-aGE5SWD75-BN34ILn9XSSbqHUMz9O4RGlY9GLUNttfhTv0JLQNsBNrgYwywVq0dA8zR2U5RonblULkcalcONZYj646f6Z6s_6p4OyosADzRNWtoJXl1D5fFxN0
CODEN ITMID4
CitedBy_id crossref_primary_10_1007_s00330_019_06051_9
crossref_primary_10_1016_j_media_2014_06_004
crossref_primary_10_1118_1_3438476
crossref_primary_10_1002_mp_14890
crossref_primary_10_1016_j_asoc_2016_08_055
crossref_primary_10_1080_21681163_2019_1692235
crossref_primary_10_1002_mp_15464
crossref_primary_10_1088_0022_3727_59_21_6355
crossref_primary_10_1177_0954411919900720
crossref_primary_10_1016_j_swevo_2024_101839
crossref_primary_10_1177_0161734620956897
crossref_primary_10_1177_0161734618780430
crossref_primary_10_7863_ultra_33_6_959
crossref_primary_10_1109_TBME_2012_2214387
crossref_primary_10_1109_TUFFC_2013_2547
crossref_primary_10_1109_ACCESS_2023_3243162
crossref_primary_10_1109_TIP_2014_2332761
crossref_primary_10_1109_TBME_2011_2127476
crossref_primary_10_1371_journal_pone_0168332
crossref_primary_10_1007_s11517_011_0781_8
crossref_primary_10_1109_TUFFC_2018_2851846
crossref_primary_10_1002_jum_15750
crossref_primary_10_1007_s11548_013_0945_0
crossref_primary_10_1016_j_compeleceng_2018_02_010
crossref_primary_10_1016_j_bspc_2014_08_012
crossref_primary_10_1364_BOE_430800
crossref_primary_10_2214_AJR_17_19211
crossref_primary_10_1109_TUFFC_2016_2578181
crossref_primary_10_3389_fonc_2022_946965
crossref_primary_10_1007_s11517_012_0883_y
crossref_primary_10_1016_j_media_2012_05_001
crossref_primary_10_1007_s11883_016_0635_9
crossref_primary_10_1016_j_ultrasmedbio_2014_10_004
crossref_primary_10_1109_TIP_2014_2371244
crossref_primary_10_35848_1347_4065_acb71a
crossref_primary_10_7567_1347_4065_ab0ba8
crossref_primary_10_1016_j_cmpb_2010_04_007
crossref_primary_10_1016_j_compmedimag_2011_06_007
crossref_primary_10_1007_s13369_018_3549_8
crossref_primary_10_1016_j_ultrasmedbio_2021_12_003
crossref_primary_10_1109_TIP_2011_2169270
crossref_primary_10_1007_s11517_014_1203_5
crossref_primary_10_1520_JTE20160214
crossref_primary_10_1016_j_ultrasmedbio_2014_08_006
crossref_primary_10_7567_JJAP_57_07LB17
crossref_primary_10_1016_j_ultrasmedbio_2020_07_021
crossref_primary_10_1166_jmihi_2021_3841
crossref_primary_10_1016_j_ultras_2012_03_005
crossref_primary_10_7567_JJAP_57_07LD19
crossref_primary_10_1118_1_4943567
crossref_primary_10_1016_j_compmedimag_2013_08_002
crossref_primary_10_1016_j_ultras_2011_11_009
crossref_primary_10_1016_j_riai_2013_05_011
crossref_primary_10_1016_j_riai_2013_11_009
crossref_primary_10_1016_j_ultrasmedbio_2011_01_014
crossref_primary_10_1155_2013_345968
crossref_primary_10_1007_s00247_018_4144_6
crossref_primary_10_1016_j_ultrasmedbio_2013_07_007
crossref_primary_10_1007_s11517_013_1128_4
crossref_primary_10_1016_j_compmedimag_2013_08_005
crossref_primary_10_1109_TBME_2010_2091129
crossref_primary_10_1016_j_media_2014_12_005
crossref_primary_10_1155_2013_801962
crossref_primary_10_1109_ACCESS_2020_3014673
crossref_primary_10_1002_jum_14566
crossref_primary_10_1109_TMI_2014_2372784
crossref_primary_10_1155_2012_481923
crossref_primary_10_1243_09544119JEIM604
crossref_primary_10_1121_1_4711005
crossref_primary_10_1016_j_patrec_2016_12_002
crossref_primary_10_1016_j_compmedimag_2013_09_004
crossref_primary_10_1007_s40846_020_00586_9
crossref_primary_10_1016_j_ultras_2022_106758
crossref_primary_10_1007_s11760_013_0578_3
crossref_primary_10_1177_08465371221134055
crossref_primary_10_1016_j_bspc_2017_08_009
crossref_primary_10_1016_j_ultrasmedbio_2017_01_025
crossref_primary_10_1007_s40846_015_0074_z
crossref_primary_10_1016_j_media_2013_10_002
crossref_primary_10_1109_TUFFC_2014_6689775
crossref_primary_10_1016_j_media_2013_05_009
crossref_primary_10_1016_j_neucom_2014_09_066
crossref_primary_10_1109_TMI_2012_2190617
crossref_primary_10_35848_1347_4065_acbb11
crossref_primary_10_1109_TMI_2015_2479455
Cites_doi 10.1177/1051228404264935
10.1007/PL00010988
10.1109/TIP.2005.851710
10.1109/4235.735430
10.2307/2333004
10.1016/S0167-8655(02)00176-9
10.2307/2291223
10.1109/42.251119
10.1016/B978-0-08-009306-2.50005-4
10.1109/TMI.2006.881376
10.1109/TUFFC.2003.1193628
10.1109/42.222674
10.1109/TMI.2006.872142
10.1093/biostatistics/3.2.213
10.1214/aoap/1015961163
10.1111/j.2517-6161.1986.tb01412.x
10.1016/j.ultrasmedbio.2005.11.012
10.1016/S0167-8655(02)00181-2
10.1088/1464-4258/1/S/306
10.1109/TPAMI.2007.1157
10.1109/58.842062
10.1007/11566465_40
10.1214/aoms/1177703862
10.1109/34.232073
10.1007/978-3-540-45087-0_21
10.1109/TAP.1976.1141451
10.1109/TBME.2005.857665
10.1109/TMI.2004.825602
10.1109/TBME.2005.855717
10.1159/000097034
10.1109/TMI.2006.877092
10.1152/ajpheart.00729.2002
10.1007/978-1-4684-0510-1
10.1111/j.2517-6161.1977.tb01600.x
10.1007/978-3-540-39903-2_53
10.1109/T-SU.1983.31404
10.1016/S0301-5629(99)00139-8
10.1214/ss/1009212814
10.1364/JOSAA.4.000910
10.1109/42.41487
10.1109/42.481438
10.1007/978-1-4757-4286-2
10.1214/aos/1176345353
10.1109/TIP.2006.877522
10.1117/12.7973900
10.1364/JOSAA.4.001764
10.1098/rspa.1946.0056
10.1109/TMI.2003.822825
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2009
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2009
DBID 97E
RIA
RIE
AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
7QF
7QO
7QQ
7SC
7SE
7SP
7SR
7TA
7TB
7U5
8BQ
8FD
F28
FR3
H8D
JG9
JQ2
KR7
L7M
L~C
L~D
NAPCQ
P64
7X8
DOI 10.1109/TMI.2008.929098
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005-present
IEEE All-Society Periodicals Package (ASPP) 1998-Present
IEEE/IET Electronic Library (IEL)
CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
Aluminium Industry Abstracts
Biotechnology Research Abstracts
Ceramic Abstracts
Computer and Information Systems Abstracts
Corrosion Abstracts
Electronics & Communications Abstracts
Engineered Materials Abstracts
Materials Business File
Mechanical & Transportation Engineering Abstracts
Solid State and Superconductivity Abstracts
METADEX
Technology Research Database
ANTE: Abstracts in New Technology & Engineering
Engineering Research Database
Aerospace Database
Materials Research Database
ProQuest Computer Science Collection
Civil Engineering Abstracts
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
Nursing & Allied Health Premium
Biotechnology and BioEngineering Abstracts
MEDLINE - Academic
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
Materials Research Database
Civil Engineering Abstracts
Aluminium Industry Abstracts
Technology Research Database
Computer and Information Systems Abstracts – Academic
Mechanical & Transportation Engineering Abstracts
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Ceramic Abstracts
Materials Business File
METADEX
Biotechnology and BioEngineering Abstracts
Computer and Information Systems Abstracts Professional
Aerospace Database
Nursing & Allied Health Premium
Engineered Materials Abstracts
Biotechnology Research Abstracts
Solid State and Superconductivity Abstracts
Engineering Research Database
Corrosion Abstracts
Advanced Technologies Database with Aerospace
ANTE: Abstracts in New Technology & Engineering
MEDLINE - Academic
DatabaseTitleList Engineering Research Database
Engineering Research Database

Materials Research Database
MEDLINE
MEDLINE - Academic
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
– sequence: 3
  dbid: RIE
  name: IEEE/IET Electronic Library (IEL) (UW System Shared)
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Engineering
EISSN 1558-254X
EndPage 229
ExternalDocumentID 2295050231
19068423
10_1109_TMI_2008_929098
4591386
Genre orig-research
Research Support, Non-U.S. Gov't
Journal Article
GroupedDBID ---
-DZ
-~X
.GJ
0R~
29I
4.4
53G
5GY
5RE
5VS
6IK
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABQJQ
ABVLG
ACGFO
ACGFS
ACIWK
ACNCT
ACPRK
AENEX
AETIX
AFRAH
AGQYO
AGSQL
AHBIQ
AI.
AIBXA
AKJIK
AKQYR
ALLEH
ALMA_UNASSIGNED_HOLDINGS
ASUFR
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
DU5
EBS
EJD
F5P
HZ~
H~9
IBMZZ
ICLAB
IFIPE
IFJZH
IPLJI
JAVBF
LAI
M43
MS~
O9-
OCL
P2P
PQQKQ
RIA
RIE
RNS
RXW
TAE
TN5
VH1
AAYXX
CITATION
AAYOK
CGR
CUY
CVF
ECM
EIF
NPM
RIG
7QF
7QO
7QQ
7SC
7SE
7SP
7SR
7TA
7TB
7U5
8BQ
8FD
F28
FR3
H8D
JG9
JQ2
KR7
L7M
L~C
L~D
NAPCQ
P64
7X8
ID FETCH-LOGICAL-c405t-1871cd73502205d86bbe53ea8a7e7c5412aedbbe338efd91063965eda21e5de73
IEDL.DBID RIE
ISSN 0278-0062
1558-254X
IngestDate Sat Sep 27 18:16:06 EDT 2025
Wed Oct 01 12:24:01 EDT 2025
Sat Sep 27 20:02:10 EDT 2025
Mon Jun 30 06:32:03 EDT 2025
Thu Apr 03 07:03:35 EDT 2025
Thu Apr 24 22:57:04 EDT 2025
Wed Oct 01 03:55:17 EDT 2025
Tue Aug 26 16:47:41 EDT 2025
IsPeerReviewed false
IsScholarly true
Issue 2
Keywords Exploration Selection algorithm
B-mode
Bayesian model
mixtures of gamma distributions
segmentation
Expectation Maximization algorithm
carotid artery
ultrasound
mixtures of Nakagami distributions
stochastic optimization
Language English
License https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c405t-1871cd73502205d86bbe53ea8a7e7c5412aedbbe338efd91063965eda21e5de73
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
PMID 19068423
PQID 857452051
PQPubID 23462
PageCount 15
ParticipantIDs pubmed_primary_19068423
proquest_journals_857452051
proquest_miscellaneous_66881658
crossref_citationtrail_10_1109_TMI_2008_929098
crossref_primary_10_1109_TMI_2008_929098
proquest_miscellaneous_867734570
ieee_primary_4591386
proquest_miscellaneous_20505205
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2009-02-01
PublicationDateYYYYMMDD 2009-02-01
PublicationDate_xml – month: 02
  year: 2009
  text: 2009-02-01
  day: 01
PublicationDecade 2000
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: New York
PublicationTitle IEEE transactions on medical imaging
PublicationTitleAbbrev TMI
PublicationTitleAlternate IEEE Trans Med Imaging
PublicationYear 2009
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
ref12
ref15
ref14
ref55
ref10
boukerroui (ref42) 2004; 24
ref17
ref16
rudin (ref59) 1987
ref19
ref18
ref51
ref50
destrempes (ref45) 2002
ref46
ref48
ref47
ref41
ref43
zwiebel (ref56) 2005
berger (ref57) 1985
ref8
ref7
ref9
ref4
ref3
titterington (ref27) 1985
ref6
ref5
jeffreys (ref54) 1961
ref40
destrempes (ref44) 2006
ref35
ref34
ref31
ref30
ref33
ref32
ref2
ref1
fisher (ref58) 1956
ref39
ref38
ref24
ref23
ref26
ref25
ref20
jeffreys (ref53) 1946; 186
ref22
ref21
hoeting (ref37) 1999; 14
ref28
ref29
madigan (ref36) 1996
robert (ref52) 2001
dempster (ref11) 1977; 39
destrempes (ref49) 2002
References_xml – ident: ref35
  doi: 10.1177/1051228404264935
– ident: ref5
  doi: 10.1007/PL00010988
– ident: ref46
  doi: 10.1109/TIP.2005.851710
– ident: ref43
  doi: 10.1109/4235.735430
– year: 1956
  ident: ref58
  publication-title: Statistical Methods and Scientific Inference
– ident: ref14
  doi: 10.2307/2333004
– ident: ref23
  doi: 10.1016/S0167-8655(02)00176-9
– ident: ref31
  doi: 10.2307/2291223
– ident: ref13
  doi: 10.1109/42.251119
– year: 1987
  ident: ref59
  publication-title: Real and Complex Analysis
– ident: ref17
  doi: 10.1016/B978-0-08-009306-2.50005-4
– ident: ref21
  doi: 10.1109/TMI.2006.881376
– year: 1985
  ident: ref27
  publication-title: Statistical Analysis of Finite Mixture Distributions
– year: 2005
  ident: ref56
  publication-title: Introduction to Vascular Ultrasonography
– ident: ref18
  doi: 10.1109/TUFFC.2003.1193628
– ident: ref39
  doi: 10.1109/42.222674
– ident: ref7
  doi: 10.1109/TMI.2006.872142
– ident: ref24
  doi: 10.1093/biostatistics/3.2.213
– ident: ref25
  doi: 10.1214/aoap/1015961163
– ident: ref41
  doi: 10.1111/j.2517-6161.1986.tb01412.x
– year: 2001
  ident: ref52
  publication-title: The Bayesian Choice
– ident: ref20
  doi: 10.1016/j.ultrasmedbio.2005.11.012
– volume: 24
  start-page: 779
  year: 2004
  ident: ref42
  article-title: Segmentation of ultrasound images?multiresolution 2-d and 3-D algorithm based on global and local statistics
  publication-title: Pattern Recognit Lett
  doi: 10.1016/S0167-8655(02)00181-2
– volume: 14
  start-page: 382
  year: 1999
  ident: ref37
  article-title: bayesian model averaging: a tutorial (with discussion)
  publication-title: Stat Sci
– ident: ref29
  doi: 10.1088/1464-4258/1/S/306
– ident: ref48
  doi: 10.1109/TPAMI.2007.1157
– ident: ref16
  doi: 10.1109/58.842062
– year: 2002
  ident: ref45
  publication-title: D tection non-supervis e de contours et localisation de formes l'aide de mod les statistiques
– ident: ref9
  doi: 10.1007/11566465_40
– ident: ref28
  doi: 10.1214/aoms/1177703862
– ident: ref55
  doi: 10.1109/34.232073
– ident: ref22
  doi: 10.1007/978-3-540-45087-0_21
– year: 2006
  ident: ref44
  publication-title: Estimation de param tres de champs Markoviens cach s avec applications la segmentation d'images et la localisation de formes
– ident: ref15
  doi: 10.1109/TAP.1976.1141451
– ident: ref50
  doi: 10.1109/TBME.2005.857665
– ident: ref8
  doi: 10.1109/TMI.2004.825602
– ident: ref51
  doi: 10.1109/TBME.2005.855717
– ident: ref1
  doi: 10.1159/000097034
– ident: ref26
  doi: 10.1109/TMI.2006.877092
– ident: ref34
  doi: 10.1152/ajpheart.00729.2002
– start-page: 77
  year: 1996
  ident: ref36
  publication-title: Integrating Multiple Learned Models (IMLM-96)
– year: 1961
  ident: ref54
  publication-title: Theory of Probabiliy
– ident: ref33
  doi: 10.1007/978-1-4684-0510-1
– volume: 39
  start-page: 1
  year: 1977
  ident: ref11
  article-title: Maximum likelihood from incomplete data via the EM algorithm
  publication-title: J R Statist Soc (Series B)
  doi: 10.1111/j.2517-6161.1977.tb01600.x
– ident: ref6
  doi: 10.1007/978-3-540-39903-2_53
– ident: ref10
  doi: 10.1109/T-SU.1983.31404
– ident: ref4
  doi: 10.1016/S0301-5629(99)00139-8
– ident: ref38
  doi: 10.1214/ss/1009212814
– ident: ref30
  doi: 10.1364/JOSAA.4.000910
– ident: ref40
  doi: 10.1109/42.41487
– ident: ref3
  doi: 10.1109/42.481438
– year: 1985
  ident: ref57
  publication-title: Statistical Decision Theory and Bayesian Analysis
  doi: 10.1007/978-1-4757-4286-2
– ident: ref32
  doi: 10.1214/aos/1176345353
– ident: ref47
  doi: 10.1109/TIP.2006.877522
– ident: ref12
  doi: 10.1117/12.7973900
– ident: ref19
  doi: 10.1364/JOSAA.4.001764
– start-page: 66
  year: 2002
  ident: ref49
  article-title: unsupervised localization of shapes using statistical models
  publication-title: 4th IASTED Int Conf Signal Image Process
– volume: 186
  start-page: 453
  year: 1946
  ident: ref53
  article-title: An invariant form for the prior probability in estimation problems
  publication-title: Proc R Soc London (Ser A)
  doi: 10.1098/rspa.1946.0056
– ident: ref2
  doi: 10.1109/TMI.2003.822825
SSID ssj0014509
Score 2.3345387
Snippet The goal of this work is to perform a segmentation of the intimamedia thickness (IMT) of carotid arteries in view of computing various dynamical properties of...
SourceID proquest
pubmed
crossref
ieee
SourceType Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 215
SubjectTerms Algorithms
B -mode
Bayes Theorem
Bayesian model
Blood
Carotid arteries
Carotid Arteries - diagnostic imaging
carotid artery
Distributed computing
Elasticity
expectation maximization (EM) algorithm
exploration selection algorithm
Humans
Image Processing, Computer-Assisted - methods
Image segmentation
Maximum a posteriori estimation
Maximum likelihood estimation
mixtures of gamma distributions
mixtures of Nakagami distributions
Models, Statistical
Nakagami distribution
segmentation
stochastic optimization
Stochastic Processes
Studies
Ultrasonic imaging
Ultrasonography - methods
ultrasound
Title Segmentation in Ultrasonic B-Mode Images of Healthy Carotid Arteries Using Mixtures of Nakagami Distributions and Stochastic Optimization
URI https://ieeexplore.ieee.org/document/4591386
https://www.ncbi.nlm.nih.gov/pubmed/19068423
https://www.proquest.com/docview/857452051
https://www.proquest.com/docview/20505205
https://www.proquest.com/docview/66881658
https://www.proquest.com/docview/867734570
Volume 28
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVIEE
  databaseName: IEEE/IET Electronic Library (IEL) (UW System Shared)
  customDbUrl:
  eissn: 1558-254X
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0014509
  issn: 0278-0062
  databaseCode: RIE
  dateStart: 19820101
  isFulltext: true
  titleUrlDefault: https://ieeexplore.ieee.org/
  providerName: IEEE
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3JbtRAEC0lOSA4sCQsJix94MABT7y1u_vIFiVIDodkpNxGvU0ySsZGsUcC_oC_pnoZs4iRuFl22e5SdbtfuapeAbzSDDGsEipFdKxdSY5JOW6sqWCFRACshfEEps1JfTStPp3T8y14M9bCWGt98pmduEMfyzedXrlfZQcVFXnJ623YZkyEWq0xYlDRkM5ROMbYrC4ijU-eiYOz5jgkTSIUyITv0CcyF38q_9iMfHeVzUDTbziH96BZDzXkmVxNVoOa6O9_sTj-ry734W5EnuRtmCoPYMu2u3DnNz7CXbjVxEj7Hvw4tRfLWJfUkkVLptfDjewdkS55l7oOauR4id-innRzEmqZvhGXPTIsjHuH40_uiU9IIM3iq4tTeNETeSUv5HJBPjjG3thsqyeyNeR06PSldLzR5DN-yJaxQvQhTA8_nr0_SmPbhlQj-hvSHH0wbVhJfRGv4bVSlpZWcsks07TKC2kNnkPn2M4NwhUESTW1Rha5pcay8hHstF1rnwChc86NypS186JCT0lRoatS50roTPEyS2Cytt9MR05z11rjeuZ9m0zM0Pah02awfQKvxxu-BDqPzaJ7zmqjWDRYAvvrCTKLy72fccoqisrmCbwcr-I6dcEX2dpu1eOTXcvAjG6WqGvOcwSECZANEo57sKwoQ70fh6n5S4k4o5_-e9T7cDuEwVwezjPYGW5W9jmiqUG98MvoJ5jmGuE
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3JbtRAEC2FILEcWBIWEyB94MABT7y17T6yRTMQD4fMSLlZvU0YJWOj2CMBf8BfU72MWcRI3Cy7bHeput2vXFWvAF7IAjGsYCJEdCxNSY4KS9xYQ1YkHAGwZMoSmFbTfDzPPpzRsx14NdTCaK1t8pkemUMby1etXJtfZUcZZXFa5tfgOkWvonDVWkPMIKMuoSMxnLFRnnginzhiR7Nq4tImEQxEzPboY5GJQKV_bEe2v8p2qGm3nOO7UG0G6zJNLkbrXozk9794HP9Xm3twx2NP8tpNlvuwo5s9uP0bI-Ee3Kh8rH0ffpzq85WvTGrIsiHzy_6Kd4ZKl7wJTQ81Mlnh16gj7YK4aqZvxOSP9Etl3mEYlDtiUxJItfxqIhVWdMov-DlfLck7w9nr2211hDeKnPat_MwNczT5hJ-yla8RfQDz4_ezt-PQN24IJeK_PozRC5OqSKkt41VlLoSmqeYlL3QhaRYnXCs8h-6xXigELAiTcqoVT2JNlS7Sh7DbtI1-DIQuylKJSGi9SDL0lQRlMktlLJiMRJlGAYw29qulZzU3zTUua-vdRKxG27tem872AbwcbvjiCD22i-4bqw1i3mABHGwmSO0XfFeXtMgoKhsHcDhcxZVqwi-80e26wyebpoER3S6R52UZIyQMgGyRMOyDaUYL1PuRm5q_lPAz-sm_R30IN8ez6qQ-mUw_HsAtFxQzWTlPYbe_WutniK168dwuqZ-N1h4y
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=Segmentation+in+ultrasonic+B-mode+images+of+healthy+carotid+arteries+using+mixtures+of+Nakagami+distributions+and+stochastic+optimization&rft.jtitle=IEEE+transactions+on+medical+imaging&rft.au=Destrempes%2C+Fran%C3%A7ois&rft.au=Meunier%2C+Jean&rft.au=Giroux%2C+Marie-France&rft.au=Soulez%2C+Gilles&rft.date=2009-02-01&rft.eissn=1558-254X&rft.volume=28&rft.issue=2&rft.spage=215&rft_id=info:doi/10.1109%2FTMI.2008.929098&rft_id=info%3Apmid%2F19068423&rft.externalDocID=19068423
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0278-0062&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0278-0062&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0278-0062&client=summon