alexa Comparison between Linear and Reverse Linear K-Space Order with Partial Fourier Fractions for Modulation Transfer Function in Dynamic Contrast-Enhanced Magnetic Resonance Imaging: A Simulation Study
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
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Research Article

Comparison between Linear and Reverse Linear K-Space Order with Partial Fourier Fractions for Modulation Transfer Function in Dynamic Contrast-Enhanced Magnetic Resonance Imaging: A Simulation Study

Takatsu Y1,2*, Ueyama T3, Miyati T2 and Yamamura K2,4*

1Department of Radiology, Osaka Red Cross Hospital, 5-30 Fudegasaki, Tennouji-ku, Osaka, 543-8555, Japan

2Division of Health Sciences, Graduate School of Medical Science, Kanazawa University, Japan

3Department of Radiology, The University of Tokyo Hospital, Japan

4Department of Radiology, Osaka Medical College Hospital, Japan

*Corresponding Author:
Yasuo Takatsu
Division of Health Sciences, Graduate
School of Medical Science, Kanazawa University, Japan
Tel: +81667745111
Fax: +81667745131
E-mail: [email protected]

Received date: May 12, 2017; Accepted date: May 23, 2017; Published date: June 01, 2017

Citation: Takatsu Y, Ueyama T, Miyati T, Yamamura K (2017) Comparison between Linear and Reverse Linear K-Space Order with Partial Fourier Fractions for Modulation Transfer Function in Dynamic Contrast-Enhanced Magnetic Resonance Imaging: A Simulation Study. J Comput Sci Syst Biol 10:028-031. doi:10.4172/jcsb.1000245

Copyright: © 2017 Takatsu Y, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Objective: To assess how the modulation transfer function (MTF) was influenced by the k-space trajectory with partial Fourier fractions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), calculating MTF using computer simulations.

Methods: Reference data for signal intensity were acquired using breast model at different concentrations and used to create a digital phantom. Frequency images were created by fast Fourier transform, divided into parts, and a new image formed by taking one part from each. The MTFs were then calculated. Three linear signal intensity slope models (low, medium, and high) and three exponential curve models (slow, medium, and rapid) were created using the reference data.

Results: The smaller the partial Fourier fraction used, the faster the decline in MTF. The MTF of the three linear slope models showed that the higher gradient of the slope used, the more rapid was the decline in MTF. The MTF of all three exponential curve models were more gradually decreasing than all three linear slope models.

Conclusion: The MTF was influenced by the k-space trajectory with partial Fourier fractions in DCE-MRI using computer simulations. The reverse linear order was found to be less influenced than the linear order by the partial Fourier fraction.

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