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...
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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. |
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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. 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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> |
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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 |
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