Motion Adaptive Wavelet Thresholding for Recovery of Compressively Sampled Static and Dynamic MR Images
- Авторы: Bilal M.1, Shah J.A.2, Qureshi I.M.3, Ahmed A.H.3
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Учреждения:
- Department of Electrical Engineering, Faculty of Engineering and Technology, International Islamic University Islamabad
- Department of Electrical Engineering, UniKL BMI
- Department of Electronic Engineering, Institute of Signals, Systems and Soft Computing (ISSS), Air University
- Выпуск: Том 49, № 9 (2018)
- Страницы: 1027-1041
- Раздел: Original Paper
- URL: https://journals.rcsi.science/0937-9347/article/view/248115
- DOI: https://doi.org/10.1007/s00723-018-1022-1
- ID: 248115
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Аннотация
Iterative shrinkage algorithms like parallel coordinate descent and separable surrogate functional use wavelet thresholding with uniform and empirically selected threshold values to recover the under-sampled magnetic resonance (MR) images. In this paper, an adaptive thresholding parameter, for the recovery of static and dynamic MR images, is derived and used in wavelet domain shrinkage. A modified iterative shrinkage thresholding algorithm based on the derived parameter is also proposed. Simulation results show that adaptive wavelet thresholding yields significantly higher signal-to-noise ratio and correlation than the fixed thresholding value. The algorithm based on the adaptive threshold is experimentally tested for static and dynamic MR images with varying acceleration rates, and it has been shown that it outperforms the fixed thresholding value algorithm.
Об авторах
Muhammad Bilal
Department of Electrical Engineering, Faculty of Engineering and Technology, International Islamic University Islamabad
Автор, ответственный за переписку.
Email: m.bilal@iiu.edu.pk
ORCID iD: 0000-0001-8768-3526
Пакистан, Islamabad
Jawad Shah
Department of Electrical Engineering, UniKL BMI
Автор, ответственный за переписку.
Email: jawad@unikl.edu.my
Малайзия, Kuala Lumpur
I. Qureshi
Department of Electronic Engineering, Institute of Signals, Systems and Soft Computing (ISSS), Air University
Email: jawad@unikl.edu.my
Пакистан, Islamabad
Abdul Ahmed
Department of Electronic Engineering, Institute of Signals, Systems and Soft Computing (ISSS), Air University
Email: jawad@unikl.edu.my
Пакистан, Islamabad
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