Title :
Parallel generalized series MRI: algorithm and application to cancer imaging
Author :
Xu, Dan ; Ying, Leslie ; Liang, Zhi-Pei
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Champaign, IL, USA
Abstract :
MRI is a relatively slow imaging technique. Although imaging speeds have increased dramatically over the last three decades, many clinical and research applications, ranging from contrast-enhanced dynamic imaging of breast tumors to cardiac imaging, require still faster imaging methods. To address this problem, this paper presents a novel algorithm to integrate generalized series (OS) imaging with parallel imaging using multiple receiver coils. This algorithm takes advantage of both the conventional parallel data acquisition scheme and the GS model-based reduced-scan imaging method to achieve higher spatiotemporal resolution in dynamic imaging. The algorithm has been validated using both simulated and experimental data from dynamic contrast-enhanced MRI experiments, which produced excellent results. We expect the algorithm to be useful for a number of dynamic imaging applications, especially contrast-enhanced imaging of tumors.
Keywords :
biomedical MRI; cancer; cardiology; data acquisition; image resolution; medical image processing; spatiotemporal phenomena; tumours; breast tumor; cancer imaging; cardiac imaging; contrast-enhanced dynamic imaging; data acquisition scheme; magnetic resonance imaging; model-based reduced-scan imaging; multiple receiver coils; parallel generalized series MRI; spatiotemporal resolution; Application software; Cancer; Coils; Data acquisition; High-resolution imaging; Image resolution; Magnetic resonance imaging; Neoplasms; Spatiotemporal phenomena; Thyristors;
Conference_Titel :
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-8439-3
DOI :
10.1109/IEMBS.2004.1403344