Multi-modal cardiac image fusion and visualization on the GPU
The main motivation of this project is to derive and present an integrated cardiac model, based on information obtained using two different imaging modalities: 3D echocardiography (3D echo) and cardiac magnetic resonance imaging (CMR). Since 3D echo allows for volumetric and functional measurements...
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creator | Kiss, G. Asen, Jon Petter Bogaert, J. Amundsen, B. Claus, P. D'hooge, J. Torp, H. G. |
description | The main motivation of this project is to derive and present an integrated cardiac model, based on information obtained using two different imaging modalities: 3D echocardiography (3D echo) and cardiac magnetic resonance imaging (CMR). Since 3D echo allows for volumetric and functional measurements in real-time, while CMR can produce anatomically accurate recordings of morphology and function (cine imaging), perfusion (first-pass imaging) and tissue characterization (such as edema (T2 STIR) or scar (late enhancement imaging)), combining them should benefit myocardial viability assessment and ischemia diagnosis. Results: The computed left ventricular regional parameters show a significant difference between normal and dysfunctional regions. Average contour deformation errors for CMR data are in the range of inter-observer variability. A good visual alignment between 3D echo and CMR data was achievable for all cases. Conclusion: Combining multi-modal anatomical and functional information allows for a quick visual assessment of datasets obtained the same day or during longitudinal studies. Current work includes further integration of 3D echo and CMR data and possibly of other imaging modalities (e.g. CT). |
doi_str_mv | 10.1109/ULTSYM.2011.0062 |
format | Conference Proceeding |
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G.</creator><creatorcontrib>Kiss, G. ; Asen, Jon Petter ; Bogaert, J. ; Amundsen, B. ; Claus, P. ; D'hooge, J. ; Torp, H. G.</creatorcontrib><description>The main motivation of this project is to derive and present an integrated cardiac model, based on information obtained using two different imaging modalities: 3D echocardiography (3D echo) and cardiac magnetic resonance imaging (CMR). Since 3D echo allows for volumetric and functional measurements in real-time, while CMR can produce anatomically accurate recordings of morphology and function (cine imaging), perfusion (first-pass imaging) and tissue characterization (such as edema (T2 STIR) or scar (late enhancement imaging)), combining them should benefit myocardial viability assessment and ischemia diagnosis. Results: The computed left ventricular regional parameters show a significant difference between normal and dysfunctional regions. Average contour deformation errors for CMR data are in the range of inter-observer variability. A good visual alignment between 3D echo and CMR data was achievable for all cases. Conclusion: Combining multi-modal anatomical and functional information allows for a quick visual assessment of datasets obtained the same day or during longitudinal studies. 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G.</creatorcontrib><title>Multi-modal cardiac image fusion and visualization on the GPU</title><title>2011 IEEE International Ultrasonics Symposium</title><addtitle>ULTSYM</addtitle><description>The main motivation of this project is to derive and present an integrated cardiac model, based on information obtained using two different imaging modalities: 3D echocardiography (3D echo) and cardiac magnetic resonance imaging (CMR). Since 3D echo allows for volumetric and functional measurements in real-time, while CMR can produce anatomically accurate recordings of morphology and function (cine imaging), perfusion (first-pass imaging) and tissue characterization (such as edema (T2 STIR) or scar (late enhancement imaging)), combining them should benefit myocardial viability assessment and ischemia diagnosis. Results: The computed left ventricular regional parameters show a significant difference between normal and dysfunctional regions. Average contour deformation errors for CMR data are in the range of inter-observer variability. A good visual alignment between 3D echo and CMR data was achievable for all cases. Conclusion: Combining multi-modal anatomical and functional information allows for a quick visual assessment of datasets obtained the same day or during longitudinal studies. Current work includes further integration of 3D echo and CMR data and possibly of other imaging modalities (e.g. CT).</description><subject>Computational modeling</subject><subject>Graphics processing unit</subject><subject>Heart</subject><subject>Image registration</subject><subject>Imaging</subject><subject>Manuals</subject><subject>Myocardium</subject><issn>1051-0117</issn><isbn>9781457712531</isbn><isbn>1457712539</isbn><isbn>9781457712524</isbn><isbn>1457712512</isbn><isbn>9781457712517</isbn><isbn>1457712520</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVjk1LAzEYhCMqWGvvgpf8gV3fN19v9uBBilZhi4Ldg6eSbhKNbFvZD0F_vSt6EQaGGR6GYewcIUeE4rIqV0_Py1wAYg5gxAGbFWRRaSIUWqjDf1niEZsgaMxGnk7Yade9AQgYwQm7Wg5Nn7Lt3ruG1671ydU8bd1L4HHo0n7H3c7zj9QNrklfrv9pRvWvgS8eqzN2HF3ThdmfT1l1e7Oa32Xlw-J-fl1mCUn3maXoTE2ejMXgag0EESNpC1FvaqkKQUrZSCAleV2gchbRxmDMRgRwXk7Zxe9uCiGs39vxYPu5NqKQElF-A3asSh4</recordid><startdate>201110</startdate><enddate>201110</enddate><creator>Kiss, G.</creator><creator>Asen, Jon Petter</creator><creator>Bogaert, J.</creator><creator>Amundsen, B.</creator><creator>Claus, P.</creator><creator>D'hooge, J.</creator><creator>Torp, H. G.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201110</creationdate><title>Multi-modal cardiac image fusion and visualization on the GPU</title><author>Kiss, G. ; Asen, Jon Petter ; Bogaert, J. ; Amundsen, B. ; Claus, P. ; D'hooge, J. ; Torp, H. 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G.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kiss, G.</au><au>Asen, Jon Petter</au><au>Bogaert, J.</au><au>Amundsen, B.</au><au>Claus, P.</au><au>D'hooge, J.</au><au>Torp, H. G.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Multi-modal cardiac image fusion and visualization on the GPU</atitle><btitle>2011 IEEE International Ultrasonics Symposium</btitle><stitle>ULTSYM</stitle><date>2011-10</date><risdate>2011</risdate><spage>254</spage><epage>257</epage><pages>254-257</pages><issn>1051-0117</issn><isbn>9781457712531</isbn><isbn>1457712539</isbn><eisbn>9781457712524</eisbn><eisbn>1457712512</eisbn><eisbn>9781457712517</eisbn><eisbn>1457712520</eisbn><abstract>The main motivation of this project is to derive and present an integrated cardiac model, based on information obtained using two different imaging modalities: 3D echocardiography (3D echo) and cardiac magnetic resonance imaging (CMR). Since 3D echo allows for volumetric and functional measurements in real-time, while CMR can produce anatomically accurate recordings of morphology and function (cine imaging), perfusion (first-pass imaging) and tissue characterization (such as edema (T2 STIR) or scar (late enhancement imaging)), combining them should benefit myocardial viability assessment and ischemia diagnosis. Results: The computed left ventricular regional parameters show a significant difference between normal and dysfunctional regions. Average contour deformation errors for CMR data are in the range of inter-observer variability. A good visual alignment between 3D echo and CMR data was achievable for all cases. Conclusion: Combining multi-modal anatomical and functional information allows for a quick visual assessment of datasets obtained the same day or during longitudinal studies. 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subjects | Computational modeling Graphics processing unit Heart Image registration Imaging Manuals Myocardium |
title | Multi-modal cardiac image fusion and visualization on the GPU |
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