A Super-Resolution Framework for 3-D High-Resolution and High-Contrast Imaging Using 2-D Multislice MRI
A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recove...
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| Veröffentlicht in: | IEEE transactions on medical imaging 2009-05, Vol.28 (5), p.633-644 |
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| container_title | IEEE transactions on medical imaging |
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| creator | Shilling, R.Z. Robbie, T.Q. Bailloeul, T. Mewes, K. Mersereau, R.M. Brummer, M.E. |
| description | A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach. |
| doi_str_mv | 10.1109/TMI.2008.2007348 |
| format | Article |
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Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. 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Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. 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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>Shilling, R.Z.</au><au>Robbie, T.Q.</au><au>Bailloeul, T.</au><au>Mewes, K.</au><au>Mersereau, R.M.</au><au>Brummer, M.E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Super-Resolution Framework for 3-D High-Resolution and High-Contrast Imaging Using 2-D Multislice MRI</atitle><jtitle>IEEE transactions on medical imaging</jtitle><stitle>TMI</stitle><addtitle>IEEE Trans Med Imaging</addtitle><date>2009-05-01</date><risdate>2009</risdate><volume>28</volume><issue>5</issue><spage>633</spage><epage>644</epage><pages>633-644</pages><issn>0278-0062</issn><eissn>1558-254X</eissn><coden>ITMID4</coden><abstract>A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. 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| subjects | Algorithms Brain - anatomy & histology Brain imaging Brain modeling Encoding Frequency High-resolution imaging Humans Image Processing, Computer-Assisted - methods Image reconstruction Image resolution Imaging phantoms Iterative algorithms Magnetic resonance imaging Magnetic Resonance Imaging - methods Minimally invasive surgery multislice magnetic resonance imaging (MRI) Phantoms, Imaging projection onto convex sets (POCS) Software super-resolution |
| title | A Super-Resolution Framework for 3-D High-Resolution and High-Contrast Imaging Using 2-D Multislice MRI |
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