Prostate Segmentation Using Pixel Classification and Genetic Algorithms

A Point Distribution Model (PDM) of the prostate has been constructed and used to automatically outline the contour of the gland in transurethral ultrasound images. We developed a new, two stages, method: first the PDM is fitted, using a multi-population genetic algorithm, to a binary image produced...

Full description

Saved in:
Bibliographic Details
Published inLecture notes in computer science pp. 910 - 917
Main Author ARAMBULA COSIO, Fernando
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Boundary segmentation
Computer science; control theory; systems
Exact sciences and technology
Genetic algorithms
Pattern recognition. Digital image processing. Computational geometry
Point distribution models
Image segmentation
Grey level image
Genetic algorithm
Classification
Binary image
Medical imagery
Prostate
Medical application
Pixel
Online AccessGet full text

Cover

Abstract A Point Distribution Model (PDM) of the prostate has been constructed and used to automatically outline the contour of the gland in transurethral ultrasound images. We developed a new, two stages, method: first the PDM is fitted, using a multi-population genetic algorithm, to a binary image produced from Bayesian pixel classification. This contour is then used during the second stage to seed the initial population of a simple genetic algorithm, which adjusts the PDM to the prostate boundary on a grey level image. The method is able to find good approximations of the prostate boundary in a robust manner. The method and its results on 4 prostate images are reported.
AbstractList A Point Distribution Model (PDM) of the prostate has been constructed and used to automatically outline the contour of the gland in transurethral ultrasound images. We developed a new, two stages, method: first the PDM is fitted, using a multi-population genetic algorithm, to a binary image produced from Bayesian pixel classification. This contour is then used during the second stage to seed the initial population of a simple genetic algorithm, which adjusts the PDM to the prostate boundary on a grey level image. The method is able to find good approximations of the prostate boundary in a robust manner. The method and its results on 4 prostate images are reported.
Author Cosío, Fernando Arámbula
Author_xml – sequence: 1
  givenname: Fernando
  surname: ARAMBULA COSIO
  fullname: ARAMBULA COSIO, Fernando
  organization: Lab. de Análisis de Imágenes y Visualización, CCADET, UNAM, México, D.F., 04510, Mexico
BackLink http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17416146$$DView record in Pascal Francis
BookMark eNpNkLFOwzAQhg0UibR04gWyMDAE7nx2bI9VBQWpEpWgc-QmTjCkThVngLcnVRm45T_p-3U6fVM2CV1wjN0g3COAekCUygiuCkNnbEpSAGEuCc9ZgjliRiTMBZsbpY-MG21ymLAECHhmlKArNo_xE8Yh1IarhK02fRcHO7j0zTV7F8bVdyHdRh-adOO_XZsuWxujr315QjZU6coFN_gyXbRN1_vhYx-v2WVt2-jmfzlj26fH9-Vztn5dvSwX6-zA0QyZrnXFx6-lcK7cgXU5mLquYIcVaO4USS5RUk5aouGVqHIytRElaFGVCEgzdnu6e7CxtG3d21D6WBx6v7f9T4FKjCJEPvbuTr04otC4vth13VcsEIqjyeKfSfoFAf1hGg
ContentType Book Chapter
Conference Proceeding
Copyright Springer-Verlag Berlin Heidelberg 2005
2006 INIST-CNRS
Copyright_xml – notice: Springer-Verlag Berlin Heidelberg 2005
– notice: 2006 INIST-CNRS
DBID IQODW
DOI 10.1007/11579427_93
DatabaseName Pascal-Francis
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Computer Science
Applied Sciences
EISBN 3540316531
9783540316534
EISSN 1611-3349
Editor Terashima-Marín, Hugo
Gelbukh, Alexander
de Albornoz, Álvaro
Editor_xml – sequence: 1
  givenname: Alexander
  surname: Gelbukh
  fullname: Gelbukh, Alexander
  email: gelbukh@gelbukh.com
– sequence: 2
  givenname: Álvaro
  surname: de Albornoz
  fullname: de Albornoz, Álvaro
  email: albornoz@itesm.mx
– sequence: 3
  givenname: Hugo
  surname: Terashima-Marín
  fullname: Terashima-Marín, Hugo
  email: terashima@itesm.mx
EndPage 917
ExternalDocumentID 17416146
GroupedDBID -DT
-GH
-~X
1SB
29L
2HA
2HV
5QI
875
AASHB
ABMNI
ACGFS
ADCXD
AEFIE
ALMA_UNASSIGNED_HOLDINGS
EJD
F5P
FEDTE
HVGLF
LAS
LDH
P2P
RIG
RNI
RSU
SVGTG
VI1
~02
IQODW
ID FETCH-LOGICAL-p219t-8f8d240354eecb0ae609ffd0b1d082e735251536385192d4d639f94c084dc1013
ISBN 9783540298960
3540298967
ISSN 0302-9743
IngestDate Sun Oct 22 16:03:56 EDT 2023
Tue Oct 01 20:01:46 EDT 2024
IsPeerReviewed true
IsScholarly true
Keywords Image segmentation
Grey level image
Genetic algorithm
Classification
Binary image
Medical imagery
Prostate
Medical application
Pixel
Language English
License CC BY 4.0
LinkModel OpenURL
MeetingName MICAI 2005 (advances in artificial intelligence)
MergedId FETCHMERGED-LOGICAL-p219t-8f8d240354eecb0ae609ffd0b1d082e735251536385192d4d639f94c084dc1013
PageCount 8
ParticipantIDs pascalfrancis_primary_17416146
springer_books_10_1007_11579427_93
PublicationCentury 2000
PublicationDate 2005
PublicationDateYYYYMMDD 2005-01-01
PublicationDate_xml – year: 2005
  text: 2005
PublicationDecade 2000
PublicationPlace Berlin, Heidelberg
PublicationPlace_xml – name: Berlin, Heidelberg
– name: Berlin
PublicationSeriesSubtitle Lecture Notes in Artificial Intelligence
PublicationSeriesTitle Lecture Notes in Computer Science
PublicationSubtitle 4th Mexican International Conference on Artificial Intelligence, Monterrey, Mexico, November 14-18, 2005. Proceedings
PublicationTitle Lecture notes in computer science
PublicationYear 2005
Publisher Springer Berlin Heidelberg
Springer
Publisher_xml – name: Springer Berlin Heidelberg
– name: Springer
RelatedPersons Kleinberg, Jon M.
Mattern, Friedemann
Nierstrasz, Oscar
Tygar, Dough
Steffen, Bernhard
Kittler, Josef
Vardi, Moshe Y.
Weikum, Gerhard
Sudan, Madhu
Naor, Moni
Mitchell, John C.
Terzopoulos, Demetri
Pandu Rangan, C.
Kanade, Takeo
Hutchison, David
RelatedPersons_xml – sequence: 1
  givenname: David
  surname: Hutchison
  fullname: Hutchison, David
  organization: Lancaster University, UK
– sequence: 2
  givenname: Takeo
  surname: Kanade
  fullname: Kanade, Takeo
  organization: Carnegie Mellon University, Pittsburgh, USA
– sequence: 3
  givenname: Josef
  surname: Kittler
  fullname: Kittler, Josef
  organization: University of Surrey, Guildford, UK
– sequence: 4
  givenname: Jon M.
  surname: Kleinberg
  fullname: Kleinberg, Jon M.
  organization: Cornell University, Ithaca, USA
– sequence: 5
  givenname: Friedemann
  surname: Mattern
  fullname: Mattern, Friedemann
  organization: ETH Zurich, Switzerland
– sequence: 6
  givenname: John C.
  surname: Mitchell
  fullname: Mitchell, John C.
  organization: Stanford University, CA, USA
– sequence: 7
  givenname: Moni
  surname: Naor
  fullname: Naor, Moni
  organization: Weizmann Institute of Science, Rehovot, Israel
– sequence: 8
  givenname: Oscar
  surname: Nierstrasz
  fullname: Nierstrasz, Oscar
  organization: University of Bern, Switzerland
– sequence: 9
  givenname: C.
  surname: Pandu Rangan
  fullname: Pandu Rangan, C.
  organization: Indian Institute of Technology, Madras, India
– sequence: 10
  givenname: Bernhard
  surname: Steffen
  fullname: Steffen, Bernhard
  organization: University of Dortmund, Germany
– sequence: 11
  givenname: Madhu
  surname: Sudan
  fullname: Sudan, Madhu
  organization: Massachusetts Institute of Technology, MA, USA
– sequence: 12
  givenname: Demetri
  surname: Terzopoulos
  fullname: Terzopoulos, Demetri
  organization: New York University, NY, USA
– sequence: 13
  givenname: Dough
  surname: Tygar
  fullname: Tygar, Dough
  organization: University of California, Berkeley, USA
– sequence: 14
  givenname: Moshe Y.
  surname: Vardi
  fullname: Vardi, Moshe Y.
  organization: Rice University, Houston, USA
– sequence: 15
  givenname: Gerhard
  surname: Weikum
  fullname: Weikum, Gerhard
  organization: Max-Planck Institute of Computer Science, Saarbruecken, Germany
SSID ssj0000318927
ssj0002792
Score 1.8025907
Snippet A Point Distribution Model (PDM) of the prostate has been constructed and used to automatically outline the contour of the gland in transurethral ultrasound...
SourceID pascalfrancis
springer
SourceType Index Database
Publisher
StartPage 910
SubjectTerms Applied sciences
Artificial intelligence
Boundary segmentation
Computer science; control theory; systems
Exact sciences and technology
Genetic algorithms
Pattern recognition. Digital image processing. Computational geometry
Point distribution models
Title Prostate Segmentation Using Pixel Classification and Genetic Algorithms
URI http://link.springer.com/10.1007/11579427_93
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT-MwELYKqz3AARYWLQiQteKGsso78YFDxRsVxAFW3KLEdlik0qA2lRC_nhmPE1JACPYStekj1nzJ5_E8PjO2E5dJEKoodoSOYIGSKuGkkfSdopC-8AIZFxL7nc8v4pPr8Owmuun1Bp2qpWld_JFP7_aV_A-qcA5wxS7ZLyDb_imcgNeALxwBYTi-cn5nw6y0w9Dpfv8UFQEjE9yjXL6pbu2PTQEQyWi8KG626YZqYtLjByZKagPJFfzKnPXui-kw795Jl9gYAi4p8MrtvW1VGu1SrcHl3aMe0s6aeEn6CGPxKGeNWrD94W01vqv_WVF0NIue7A1s5uKiqmnIzeYSDde8CTzufqDLZeNKqPJOuwY0rVpAw7CQIWbTxLwx6ikGpF9q2VTYildt3yXvcj6VeaBokAj9JBPBHJtLBDDct_7h2eBvG3FD-hJ-uxx3UTqRckw0GNv5YwabfG-DYjR429qJXZedK2ElbT6Bh6mkXVDepNONl3K1zBaxc4VjSwmY8gfr6dEKW2pMy61pV9hCR4RylR03-PIuvtzgyw2-fBZfDvhyiy9_wfcnuz46vNo_cez2Gs4DTFO1k5apQjXGKNRaFm6uY1eUpXILT4FfqBMUyoX5EAgavHxfhQqc2VKE0k1DJYHJgzU2P6pG-hfjMkp8T7uq9CRMAnmQgt-cwMyZe0ADMnfX2faMnbIHklLJPLPADuN19rsxXIZP1CRr5LQ71t74zJc22Xw9nuotcBXrYtveA88pbmQt
link.rule.ids 310,311,785,786,790,795,796,799,4069,4070,27958
linkProvider Library Specific Holdings
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%3Abook&rft.genre=bookitem&rft.title=MICAI+2005%3A+Advances+in+Artificial+Intelligence&rft.au=Cos%C3%ADo%2C+Fernando+Ar%C3%A1mbula&rft.atitle=Prostate+Segmentation+Using+Pixel+Classification+and+Genetic+Algorithms&rft.series=Lecture+Notes+in+Computer+Science&rft.pub=Springer+Berlin+Heidelberg&rft.isbn=9783540298960&rft.issn=0302-9743&rft.eissn=1611-3349&rft.spage=910&rft.epage=917&rft_id=info:doi/10.1007%2F11579427_93
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0302-9743&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0302-9743&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0302-9743&client=summon