Signal Interpretation of Magnetic Resonance Technology Based on Compressed Sensing

Author:

Li Li

Publisher

Springer Singapore

Reference10 articles.

1. Ahmad, K., Hassan, F.: Radial-basis-function-based nuclear magnetic resonance heavy oil viscosity prediction model for a Kuwait viscous oil field. Interpretation 4(2), 81–92 (2016)

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3. Baidyk, T., Kussul, E.: Flat image recognition in the process of microdevice assembly. Patt. Recogn. Lett. 25(1), 107–117 (2014)

4. Pantazis, D., Joshi, A.: Comparison of landmark-based and automatic methods for cortical surface registration. Neuro Image 49(3), 2479–2493 (2010)

5. Satoshi, I., Hirotoshi, A., Yoshifumi, Y.: Compressed sensing in magnetic resonance imaging using the multi-step Fresnel domain band split transformation. Magn Reson Med Sci 11(4), 243 (2012)

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