On the incorporation of shape priors into geometric active contours

A novel model for boundary determination that incorporates prior shape information into geometric active contours is presented. The basic idea of this model is to minimize the energy functional depending on the information of the image gradient and the shape of interest, so that the boundary of the...

Full description

Saved in:
Bibliographic Details
Main Authors: Yunmei Chen, Thiruvenkadam, S., Tagare, H.D., Feng Huang, Wilson, D., Geiser, E.A.
Format: Conference Proceeding
Language:English
Subjects:
Active contours
Biomedical imaging
Cardiology
Deformable models
Equations
Level set
Mathematics
Shape
Solid modeling
Ultrasonic imaging
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 152
container_issue
container_start_page 145
container_title
container_volume
creator Yunmei Chen
Thiruvenkadam, S.
Tagare, H.D.
Feng Huang
Wilson, D.
Geiser, E.A.
description A novel model for boundary determination that incorporates prior shape information into geometric active contours is presented. The basic idea of this model is to minimize the energy functional depending on the information of the image gradient and the shape of interest, so that the boundary of the object can be captured either by higher magnitude of the image gradient or by the prior knowledge of its shape. The level set form of the proposed model is also provided. We present our experimental results on some synthetic images, functional MR brain images, and ultrasound images for which the existing active contour methods are not applicable. The existence of the solution to the proposed minimization problem is also discussed.
doi_str_mv 10.1109/VLSM.2001.938893
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_938893</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>938893</ieee_id><sourcerecordid>938893</sourcerecordid><originalsourceid>FETCH-LOGICAL-i174t-5475cddbf8bfeb264609ae2260ed228334bc24480003d761e5c6de29d9e534e93</originalsourceid><addsrcrecordid>eNotj0tLxDAcxAMiqOvexVO-QGvej6MUHwuVPfjA25Im_7oRtylJFPz2Fta5DMzA8BuErihpKSX25q1_fmoZIbS13BjLT9AF0cpKyrR5P0PrUj7JIiGJ0uIcddsJ1z3gOPmU55RdjWnCacRl72bAc44pl6WtCX9AOkDN0WPna_wB7NMSf-dyiU5H91Vg_e8r9Hp_99I9Nv32YdPd9k2kWtRGCi19CMNohhEGpoQi1gFjikBgzHAuBs-EMAsdD1pRkF4FYDZYkFyA5St0fdyNALBb0A4u_-6ON_kf57VI7g</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>On the incorporation of shape priors into geometric active contours</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Yunmei Chen ; Thiruvenkadam, S. ; Tagare, H.D. ; Feng Huang ; Wilson, D. ; Geiser, E.A.</creator><creatorcontrib>Yunmei Chen ; Thiruvenkadam, S. ; Tagare, H.D. ; Feng Huang ; Wilson, D. ; Geiser, E.A.</creatorcontrib><description>A novel model for boundary determination that incorporates prior shape information into geometric active contours is presented. The basic idea of this model is to minimize the energy functional depending on the information of the image gradient and the shape of interest, so that the boundary of the object can be captured either by higher magnitude of the image gradient or by the prior knowledge of its shape. The level set form of the proposed model is also provided. We present our experimental results on some synthetic images, functional MR brain images, and ultrasound images for which the existing active contour methods are not applicable. The existence of the solution to the proposed minimization problem is also discussed.</description><identifier>ISBN: 076951278X</identifier><identifier>ISBN: 9780769512785</identifier><identifier>DOI: 10.1109/VLSM.2001.938893</identifier><language>eng</language><publisher>IEEE</publisher><subject>Active contours ; Biomedical imaging ; Cardiology ; Deformable models ; Equations ; Level set ; Mathematics ; Shape ; Solid modeling ; Ultrasonic imaging</subject><ispartof>Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision, 2001, p.145-152</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/938893$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/938893$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yunmei Chen</creatorcontrib><creatorcontrib>Thiruvenkadam, S.</creatorcontrib><creatorcontrib>Tagare, H.D.</creatorcontrib><creatorcontrib>Feng Huang</creatorcontrib><creatorcontrib>Wilson, D.</creatorcontrib><creatorcontrib>Geiser, E.A.</creatorcontrib><title>On the incorporation of shape priors into geometric active contours</title><title>Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision</title><addtitle>VLSM</addtitle><description>A novel model for boundary determination that incorporates prior shape information into geometric active contours is presented. The basic idea of this model is to minimize the energy functional depending on the information of the image gradient and the shape of interest, so that the boundary of the object can be captured either by higher magnitude of the image gradient or by the prior knowledge of its shape. The level set form of the proposed model is also provided. We present our experimental results on some synthetic images, functional MR brain images, and ultrasound images for which the existing active contour methods are not applicable. The existence of the solution to the proposed minimization problem is also discussed.</description><subject>Active contours</subject><subject>Biomedical imaging</subject><subject>Cardiology</subject><subject>Deformable models</subject><subject>Equations</subject><subject>Level set</subject><subject>Mathematics</subject><subject>Shape</subject><subject>Solid modeling</subject><subject>Ultrasonic imaging</subject><isbn>076951278X</isbn><isbn>9780769512785</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2001</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj0tLxDAcxAMiqOvexVO-QGvej6MUHwuVPfjA25Im_7oRtylJFPz2Fta5DMzA8BuErihpKSX25q1_fmoZIbS13BjLT9AF0cpKyrR5P0PrUj7JIiGJ0uIcddsJ1z3gOPmU55RdjWnCacRl72bAc44pl6WtCX9AOkDN0WPna_wB7NMSf-dyiU5H91Vg_e8r9Hp_99I9Nv32YdPd9k2kWtRGCi19CMNohhEGpoQi1gFjikBgzHAuBs-EMAsdD1pRkF4FYDZYkFyA5St0fdyNALBb0A4u_-6ON_kf57VI7g</recordid><startdate>2001</startdate><enddate>2001</enddate><creator>Yunmei Chen</creator><creator>Thiruvenkadam, S.</creator><creator>Tagare, H.D.</creator><creator>Feng Huang</creator><creator>Wilson, D.</creator><creator>Geiser, E.A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2001</creationdate><title>On the incorporation of shape priors into geometric active contours</title><author>Yunmei Chen ; Thiruvenkadam, S. ; Tagare, H.D. ; Feng Huang ; Wilson, D. ; Geiser, E.A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i174t-5475cddbf8bfeb264609ae2260ed228334bc24480003d761e5c6de29d9e534e93</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Active contours</topic><topic>Biomedical imaging</topic><topic>Cardiology</topic><topic>Deformable models</topic><topic>Equations</topic><topic>Level set</topic><topic>Mathematics</topic><topic>Shape</topic><topic>Solid modeling</topic><topic>Ultrasonic imaging</topic><toplevel>online_resources</toplevel><creatorcontrib>Yunmei Chen</creatorcontrib><creatorcontrib>Thiruvenkadam, S.</creatorcontrib><creatorcontrib>Tagare, H.D.</creatorcontrib><creatorcontrib>Feng Huang</creatorcontrib><creatorcontrib>Wilson, D.</creatorcontrib><creatorcontrib>Geiser, E.A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yunmei Chen</au><au>Thiruvenkadam, S.</au><au>Tagare, H.D.</au><au>Feng Huang</au><au>Wilson, D.</au><au>Geiser, E.A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>On the incorporation of shape priors into geometric active contours</atitle><btitle>Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision</btitle><stitle>VLSM</stitle><date>2001</date><risdate>2001</risdate><spage>145</spage><epage>152</epage><pages>145-152</pages><isbn>076951278X</isbn><isbn>9780769512785</isbn><abstract>A novel model for boundary determination that incorporates prior shape information into geometric active contours is presented. The basic idea of this model is to minimize the energy functional depending on the information of the image gradient and the shape of interest, so that the boundary of the object can be captured either by higher magnitude of the image gradient or by the prior knowledge of its shape. The level set form of the proposed model is also provided. We present our experimental results on some synthetic images, functional MR brain images, and ultrasound images for which the existing active contour methods are not applicable. The existence of the solution to the proposed minimization problem is also discussed.</abstract><pub>IEEE</pub><doi>10.1109/VLSM.2001.938893</doi><tpages>8</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 076951278X
ispartof Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision, 2001, p.145-152
issn
language eng
recordid cdi_ieee_primary_938893
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Active contours
Biomedical imaging
Cardiology
Deformable models
Equations
Level set
Mathematics
Shape
Solid modeling
Ultrasonic imaging
title On the incorporation of shape priors into geometric active contours
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T00%3A37%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=On%20the%20incorporation%20of%20shape%20priors%20into%20geometric%20active%20contours&rft.btitle=Proceedings%20IEEE%20Workshop%20on%20Variational%20and%20Level%20Set%20Methods%20in%20Computer%20Vision&rft.au=Yunmei%20Chen&rft.date=2001&rft.spage=145&rft.epage=152&rft.pages=145-152&rft.isbn=076951278X&rft.isbn_list=9780769512785&rft_id=info:doi/10.1109/VLSM.2001.938893&rft_dat=%3Cieee_6IE%3E938893%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i174t-5475cddbf8bfeb264609ae2260ed228334bc24480003d761e5c6de29d9e534e93%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=938893&rfr_iscdi=true