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Multi-scale and Multi-resolution Features for Structural Magnetic Resonance Imaging

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Pathological Brain Detection

Part of the book series: Brain Informatics and Health ((BIH))

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Abstract

This chapter is a natural follow on from Chap. 4, focusing on multiscale and multiresolution features. First, the development of signal processing from Fourier transform to short-time Fourier transform to wavelet analysis, is presented. The advantages and disadvantages of the three techniques are analyzed. Next, the question of why wavelet transform is the most popular feature extraction method is answered, by comparison between fingerprints and brain gyri.

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Authors and Affiliations

  1. School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, Henan, China

    Shui-Hua Wang & Yu-Dong Zhang

  2. School of Electronics Science and Engineering, Nanjing University, Nanjing, Jiangsu, China

    Shui-Hua Wang

  3. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

  4. Translational Imaging Division & MRI Unit, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY, USA

    Zhengchao Dong

  5. Shepherd University, Shepherdstown, WV, USA

    Preetha Phillips

  6. West Virginia School of Osteopathic Medicine, St. Lewisburg, WV, USA

    Preetha Phillips

Authors
  1. Shui-Hua Wang
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  2. Yu-Dong Zhang
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  3. Zhengchao Dong
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  4. Preetha Phillips
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Wang, SH., Zhang, YD., Dong, Z., Phillips, P. (2018). Multi-scale and Multi-resolution Features for Structural Magnetic Resonance Imaging. In: Pathological Brain Detection. Brain Informatics and Health. Springer, Singapore. https://doi.org/10.1007/978-981-10-4026-9_5

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  • DOI: https://doi.org/10.1007/978-981-10-4026-9_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4025-2

  • Online ISBN: 978-981-10-4026-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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