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Research on the Calculation of Cerebral Blood Volume Using SVD Method Based on Hankel Matrix |
Ren Ya-zi Li Ying Liu Huan |
Hebei University of Technology, Tianjin 300130,China |
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Abstract The singular value decomposition (SVD) method based on Hankel matrix is proposed in this paper to calculate cerebral blood volume (CBV) in dynamic contrast-enhanced perfusion magnetic resonance imaging. The method of differential spectral order error is proposed to determine the number of singular values. Through the theoretical derivation and simulation, the ideal filtering effect is reached. Because of the existing noise in the imaging process, the influences such as signal-to-noise ratio (SNR) and tracer delay are analyzed. The simulation results show that this method can more effectively estimate cerebral blood volume at the higher SNR(SNR=100dB) and is not affected by the tracer delay; while compared with the value of the cerebral blood volume before and after using the method, the superiority of the method is more obvious at the lower SNR (SNR=5dB). Compared with the traditional singular value decomposition, the SVD method based on Hankel matrix can estimate the cerebral blood volume accurately.
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Received: 17 July 2015
Published: 15 August 2016
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