Exploiting Quasiperiodicity in Motion Correction of Free-Breathing Myocardial Perfusion MRI

Free-breathing image acquisition is desirable in first-pass gadolinium-enhanced magnetic resonance imaging (MRI), but the breathing movements hinder the direct automatic analysis of the myocardial perfusion and qualitative readout by visual tracking. Nonrigid registration can be used to compensate f...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on medical imaging 2010-08, Vol.29 (8), p.1516-1527
Hauptverfasser: Wollny, G, Ledesma-Carbayo, M J, Kellman, P, Santos, A
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1527
container_issue 8
container_start_page 1516
container_title IEEE transactions on medical imaging
container_volume 29
creator Wollny, G
Ledesma-Carbayo, M J
Kellman, P
Santos, A
description Free-breathing image acquisition is desirable in first-pass gadolinium-enhanced magnetic resonance imaging (MRI), but the breathing movements hinder the direct automatic analysis of the myocardial perfusion and qualitative readout by visual tracking. Nonrigid registration can be used to compensate for these movements but needs to deal with local contrast and intensity changes with time. We propose an automatic registration scheme that exploits the quasiperiodicity of free breathing to decouple movement from intensity change. First, we identify and register a subset of the images corresponding to the same phase of the breathing cycle. This registration step deals with small differences caused by movement but maintains the full range of intensity change. The remaining images are then registered to synthetic references that are created as a linear combination of images belonging to the already registered subset. Because of the quasiperiodic respiratory movement, the subset images are distributed evenly over time and, therefore, the synthetic references exhibit intensities similar to their corresponding unregistered images. Thus, this second registration step needs to account only for the movement. Validation experiments were performed on data obtained from six patients, three slices per patient, and the automatically obtained perfusion profiles were compared with profiles obtained by manually segmenting the myocardium. The results show that our automatic approach is well suited to compensate for the free-breathing movement and that it achieves a significant improvement in the average Pearson correlation coefficient between manually and automatically obtained perfusion profiles before ( 0.87 ± 0.18 ) and after ( 0.96 ± 0.09 ) registration.
doi_str_mv 10.1109/TMI.2010.2049270
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_ieee_primary_5458069</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5458069</ieee_id><sourcerecordid>748939997</sourcerecordid><originalsourceid>FETCH-LOGICAL-c378t-ff6261024ceaed9d9d63e9b1bba1a938c779badb5a7838476311bd11a9513463</originalsourceid><addsrcrecordid>eNqFkc1LwzAYh4MoOj_ugiAFD56q-WqTHHVsOnD4wQ6Ch5K2bzWja2bSgvvvTd3cwYsJIQnv83tJeBA6JfiKEKyuZ9PJFcXhRjFXVOAdNCBJImOa8NddNMBUyBjjlB6gQ-_nGBOeYLWPDgLOw2ID9Db6WtbWtKZ5j5477c0SnLGlKUy7ikwTTW1rbBMNrXNQ_BxtFY0dQHzrQLcffW66soV2pdF19ASu6nyPTV8mx2iv0rWHk81-hGbj0Wx4Hz883k2GNw9xwYRs46pKaUow5QVoKFWYKQOVkzzXRCsmCyFUrss80UIyyUXKCMlLEmoJYTxlR-hy3Xbp7GcHvs0WxhdQ17oB2_lMSEEZVVL8T3KpmFKqJy_-kHPbuSb8IgsvFWEoRgKF11ThrPcOqmzpzEK7VYCyXlAWBGW9oGwjKETON427fAHlNvBrJABna8AAwLac8ETiVLFvvHeTmQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1027777931</pqid></control><display><type>article</type><title>Exploiting Quasiperiodicity in Motion Correction of Free-Breathing Myocardial Perfusion MRI</title><source>IEEE Electronic Library (IEL)</source><creator>Wollny, G ; Ledesma-Carbayo, M J ; Kellman, P ; Santos, A</creator><creatorcontrib>Wollny, G ; Ledesma-Carbayo, M J ; Kellman, P ; Santos, A</creatorcontrib><description>Free-breathing image acquisition is desirable in first-pass gadolinium-enhanced magnetic resonance imaging (MRI), but the breathing movements hinder the direct automatic analysis of the myocardial perfusion and qualitative readout by visual tracking. Nonrigid registration can be used to compensate for these movements but needs to deal with local contrast and intensity changes with time. We propose an automatic registration scheme that exploits the quasiperiodicity of free breathing to decouple movement from intensity change. First, we identify and register a subset of the images corresponding to the same phase of the breathing cycle. This registration step deals with small differences caused by movement but maintains the full range of intensity change. The remaining images are then registered to synthetic references that are created as a linear combination of images belonging to the already registered subset. Because of the quasiperiodic respiratory movement, the subset images are distributed evenly over time and, therefore, the synthetic references exhibit intensities similar to their corresponding unregistered images. Thus, this second registration step needs to account only for the movement. Validation experiments were performed on data obtained from six patients, three slices per patient, and the automatically obtained perfusion profiles were compared with profiles obtained by manually segmenting the myocardium. The results show that our automatic approach is well suited to compensate for the free-breathing movement and that it achieves a significant improvement in the average Pearson correlation coefficient between manually and automatically obtained perfusion profiles before ( 0.87 ± 0.18 ) and after ( 0.96 ± 0.09 ) registration.</description><identifier>ISSN: 0278-0062</identifier><identifier>EISSN: 1558-254X</identifier><identifier>DOI: 10.1109/TMI.2010.2049270</identifier><identifier>PMID: 20442043</identifier><identifier>CODEN: ITMID4</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Algorithms ; Biomedical engineering ; Biomedical imaging ; Blood ; Gadolinium ; Heart ; Heart - physiology ; Humans ; Image analysis ; Image Processing, Computer-Assisted - methods ; image registration ; Image segmentation ; Magnetic analysis ; Magnetic resonance imaging ; Magnetic Resonance Imaging - methods ; Movement - physiology ; myocardial perfusion ; Myocardial Perfusion Imaging - methods ; Myocardium ; Pattern Recognition, Automated - methods ; Reproducibility of Results ; Respiration ; Studies ; Tracking</subject><ispartof>IEEE transactions on medical imaging, 2010-08, Vol.29 (8), p.1516-1527</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Aug 2010</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c378t-ff6261024ceaed9d9d63e9b1bba1a938c779badb5a7838476311bd11a9513463</citedby><cites>FETCH-LOGICAL-c378t-ff6261024ceaed9d9d63e9b1bba1a938c779badb5a7838476311bd11a9513463</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5458069$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5458069$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20442043$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wollny, G</creatorcontrib><creatorcontrib>Ledesma-Carbayo, M J</creatorcontrib><creatorcontrib>Kellman, P</creatorcontrib><creatorcontrib>Santos, A</creatorcontrib><title>Exploiting Quasiperiodicity in Motion Correction of Free-Breathing Myocardial Perfusion MRI</title><title>IEEE transactions on medical imaging</title><addtitle>TMI</addtitle><addtitle>IEEE Trans Med Imaging</addtitle><description>Free-breathing image acquisition is desirable in first-pass gadolinium-enhanced magnetic resonance imaging (MRI), but the breathing movements hinder the direct automatic analysis of the myocardial perfusion and qualitative readout by visual tracking. Nonrigid registration can be used to compensate for these movements but needs to deal with local contrast and intensity changes with time. We propose an automatic registration scheme that exploits the quasiperiodicity of free breathing to decouple movement from intensity change. First, we identify and register a subset of the images corresponding to the same phase of the breathing cycle. This registration step deals with small differences caused by movement but maintains the full range of intensity change. The remaining images are then registered to synthetic references that are created as a linear combination of images belonging to the already registered subset. Because of the quasiperiodic respiratory movement, the subset images are distributed evenly over time and, therefore, the synthetic references exhibit intensities similar to their corresponding unregistered images. Thus, this second registration step needs to account only for the movement. Validation experiments were performed on data obtained from six patients, three slices per patient, and the automatically obtained perfusion profiles were compared with profiles obtained by manually segmenting the myocardium. The results show that our automatic approach is well suited to compensate for the free-breathing movement and that it achieves a significant improvement in the average Pearson correlation coefficient between manually and automatically obtained perfusion profiles before ( 0.87 ± 0.18 ) and after ( 0.96 ± 0.09 ) registration.</description><subject>Algorithms</subject><subject>Biomedical engineering</subject><subject>Biomedical imaging</subject><subject>Blood</subject><subject>Gadolinium</subject><subject>Heart</subject><subject>Heart - physiology</subject><subject>Humans</subject><subject>Image analysis</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>image registration</subject><subject>Image segmentation</subject><subject>Magnetic analysis</subject><subject>Magnetic resonance imaging</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Movement - physiology</subject><subject>myocardial perfusion</subject><subject>Myocardial Perfusion Imaging - methods</subject><subject>Myocardium</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Reproducibility of Results</subject><subject>Respiration</subject><subject>Studies</subject><subject>Tracking</subject><issn>0278-0062</issn><issn>1558-254X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNqFkc1LwzAYh4MoOj_ugiAFD56q-WqTHHVsOnD4wQ6Ch5K2bzWja2bSgvvvTd3cwYsJIQnv83tJeBA6JfiKEKyuZ9PJFcXhRjFXVOAdNCBJImOa8NddNMBUyBjjlB6gQ-_nGBOeYLWPDgLOw2ID9Db6WtbWtKZ5j5477c0SnLGlKUy7ikwTTW1rbBMNrXNQ_BxtFY0dQHzrQLcffW66soV2pdF19ASu6nyPTV8mx2iv0rWHk81-hGbj0Wx4Hz883k2GNw9xwYRs46pKaUow5QVoKFWYKQOVkzzXRCsmCyFUrss80UIyyUXKCMlLEmoJYTxlR-hy3Xbp7GcHvs0WxhdQ17oB2_lMSEEZVVL8T3KpmFKqJy_-kHPbuSb8IgsvFWEoRgKF11ThrPcOqmzpzEK7VYCyXlAWBGW9oGwjKETON427fAHlNvBrJABna8AAwLac8ETiVLFvvHeTmQ</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Wollny, G</creator><creator>Ledesma-Carbayo, M J</creator><creator>Kellman, P</creator><creator>Santos, A</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>NAPCQ</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>201008</creationdate><title>Exploiting Quasiperiodicity in Motion Correction of Free-Breathing Myocardial Perfusion MRI</title><author>Wollny, G ; Ledesma-Carbayo, M J ; Kellman, P ; Santos, A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c378t-ff6261024ceaed9d9d63e9b1bba1a938c779badb5a7838476311bd11a9513463</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Algorithms</topic><topic>Biomedical engineering</topic><topic>Biomedical imaging</topic><topic>Blood</topic><topic>Gadolinium</topic><topic>Heart</topic><topic>Heart - physiology</topic><topic>Humans</topic><topic>Image analysis</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>image registration</topic><topic>Image segmentation</topic><topic>Magnetic analysis</topic><topic>Magnetic resonance imaging</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Movement - physiology</topic><topic>myocardial perfusion</topic><topic>Myocardial Perfusion Imaging - methods</topic><topic>Myocardium</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Reproducibility of Results</topic><topic>Respiration</topic><topic>Studies</topic><topic>Tracking</topic><toplevel>online_resources</toplevel><creatorcontrib>Wollny, G</creatorcontrib><creatorcontrib>Ledesma-Carbayo, M J</creatorcontrib><creatorcontrib>Kellman, P</creatorcontrib><creatorcontrib>Santos, A</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE transactions on medical imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wollny, G</au><au>Ledesma-Carbayo, M J</au><au>Kellman, P</au><au>Santos, A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exploiting Quasiperiodicity in Motion Correction of Free-Breathing Myocardial Perfusion MRI</atitle><jtitle>IEEE transactions on medical imaging</jtitle><stitle>TMI</stitle><addtitle>IEEE Trans Med Imaging</addtitle><date>2010-08</date><risdate>2010</risdate><volume>29</volume><issue>8</issue><spage>1516</spage><epage>1527</epage><pages>1516-1527</pages><issn>0278-0062</issn><eissn>1558-254X</eissn><coden>ITMID4</coden><abstract>Free-breathing image acquisition is desirable in first-pass gadolinium-enhanced magnetic resonance imaging (MRI), but the breathing movements hinder the direct automatic analysis of the myocardial perfusion and qualitative readout by visual tracking. Nonrigid registration can be used to compensate for these movements but needs to deal with local contrast and intensity changes with time. We propose an automatic registration scheme that exploits the quasiperiodicity of free breathing to decouple movement from intensity change. First, we identify and register a subset of the images corresponding to the same phase of the breathing cycle. This registration step deals with small differences caused by movement but maintains the full range of intensity change. The remaining images are then registered to synthetic references that are created as a linear combination of images belonging to the already registered subset. Because of the quasiperiodic respiratory movement, the subset images are distributed evenly over time and, therefore, the synthetic references exhibit intensities similar to their corresponding unregistered images. Thus, this second registration step needs to account only for the movement. Validation experiments were performed on data obtained from six patients, three slices per patient, and the automatically obtained perfusion profiles were compared with profiles obtained by manually segmenting the myocardium. The results show that our automatic approach is well suited to compensate for the free-breathing movement and that it achieves a significant improvement in the average Pearson correlation coefficient between manually and automatically obtained perfusion profiles before ( 0.87 ± 0.18 ) and after ( 0.96 ± 0.09 ) registration.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>20442043</pmid><doi>10.1109/TMI.2010.2049270</doi><tpages>12</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0278-0062
ispartof IEEE transactions on medical imaging, 2010-08, Vol.29 (8), p.1516-1527
issn 0278-0062
1558-254X
language eng
recordid cdi_ieee_primary_5458069
source IEEE Electronic Library (IEL)
subjects Algorithms
Biomedical engineering
Biomedical imaging
Blood
Gadolinium
Heart
Heart - physiology
Humans
Image analysis
Image Processing, Computer-Assisted - methods
image registration
Image segmentation
Magnetic analysis
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Movement - physiology
myocardial perfusion
Myocardial Perfusion Imaging - methods
Myocardium
Pattern Recognition, Automated - methods
Reproducibility of Results
Respiration
Studies
Tracking
title Exploiting Quasiperiodicity in Motion Correction of Free-Breathing Myocardial Perfusion MRI
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T22%3A06%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Exploiting%20Quasiperiodicity%20in%20Motion%20Correction%20of%20Free-Breathing%20Myocardial%20Perfusion%20MRI&rft.jtitle=IEEE%20transactions%20on%20medical%20imaging&rft.au=Wollny,%20G&rft.date=2010-08&rft.volume=29&rft.issue=8&rft.spage=1516&rft.epage=1527&rft.pages=1516-1527&rft.issn=0278-0062&rft.eissn=1558-254X&rft.coden=ITMID4&rft_id=info:doi/10.1109/TMI.2010.2049270&rft_dat=%3Cproquest_RIE%3E748939997%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1027777931&rft_id=info:pmid/20442043&rft_ieee_id=5458069&rfr_iscdi=true