DocumentCode :
2803780
Title :
Super-resolution reconstruction of MR image sequences with contrast modeling
Author :
Haldar, Justin P. ; Hernando, Diego ; Liang, Zhi-Pei
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
fYear :
2009
fDate :
June 28 2009-July 1 2009
Firstpage :
266
Lastpage :
269
Abstract :
Quantitative MR imaging experiments (e.g., to measure relaxation and diffusion properties of tissues) often require image sequences with different contrast in each frame. However, high-resolution acquisition of each frame can lead to prohibitively long experiments. In this work, we investigate the possibility of utilizing a parametric contrast model to synthesize high-resolution information. Theoretical analysis and empirical evidence indicates that this kind of super-resolution can be possible, though robustness is dependent on a number of factors (e.g., the contrast model and the experiment design). In particular, it is found that conventional low-frequency sampling leads to significant information loss, but that alternative experiments can overcome this limitation. Experimental results are shown in the context of T2 * relaxation mapping.
Keywords :
biodiffusion; biological tissues; biomedical MRI; image reconstruction; image resolution; image sequences; medical image processing; MR image sequences; T2 * relaxation mapping; diffusion properties; high-resolution acquisition; parametric contrast modeling; quantitative MR imaging; relaxation properties; super-resolution reconstruction; tissues properties; Amplitude modulation; Biomedical imaging; Electric variables measurement; High-resolution imaging; Image reconstruction; Image resolution; Image sequences; Magnetic resonance imaging; Parameter estimation; Spatial resolution; magnetic resonance imaging; parameter estimation; sequence estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Conference_Location :
Boston, MA
ISSN :
1945-7928
Print_ISBN :
978-1-4244-3931-7
Electronic_ISBN :
1945-7928
Type :
conf
DOI :
10.1109/ISBI.2009.5193035
Filename :
5193035
Link To Document :
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