Combined Wavelet and Nonlinear Filtering for MRI Phase Images

Cruz-Enriquez, Hector; Lorenzo-Ginori, Juan V.

doi:10.1007/978-3-642-02611-9_9

Cited by 2 publications

(2 citation statements)

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“…This nonlinear vector filter, which uses similarity measures based on angular distances, was adapted to phasor processing and used to filter the complex image from which the phase is obtained. Cruz-Enriquez et al [6] extended this work by combining the nonlinear filter with wavelet techniques. They decomposed the real and imaginary components of the noisy complex signal using the Discrete Wavelet Transform (DWT) and the nonlinear vector is applied to each part, and finally, the filtered image is recovered by inverse DWT-2D transformation.…”

Section: Introductionmentioning

confidence: 99%

A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps

Sudeep

Palanisamy

Kesavadas

et al. 2016

SIViP

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Section: Introductionmentioning

confidence: 99%

A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps

Sudeep

Palanisamy

Kesavadas

et al. 2016

SIViP

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“…My research involved formulating and testing a set of algorithms using simulated, phantom, and real images, which showed improvements in the SNR (see Figure 1) and image quality (see Figure 2) when using combined methods (nonlinear ordering statistics and wavelet domain algorithms such as NLSUFM1AD, and NLSUFD1AD). [1][2][3][4][5] To work with raw real data, the phantom images used during the research were obtained with an experimental tomograph installed at the Centro de Biofísica Médica (Medical Biophysical Center) in Santiago de Cuba. Those images had to be processed in Santa Clara, 650 km away, on a small cluster of 12 power desktop computers.…”

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confidence: 99%

Making Supercomputing Available to All Cuban Researchers

Cruz-Enriquez

2018

Comput. Sci. Eng.

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Scientists in Cuba must get up to date with the latest trends and best practices in scientific computing. As a consequence of the socioeconomic and geopolitical situation in and around Cuba, a lack of financial means restricts Cuban researchers' access to the supercomputing infrastructures, techniques, and tools that are urgently needed to support the increasing use of computational tools and efficient data processing in different areas, especially those related to public health.In the following article, I recount my story as a young researcher and my efforts to make nationwide high-performance computing (HPC) services available to all Cuban scientists. This effort was motivated by my research experiences 15 years earlier. I began working with complex images acquired with a low signal-to-noise ratio (SNR), and found myself faced with the problem of phase residues, a major drawback for the bidimensional phase unwrapping process that is usually performed when processing phase images in several health-related applications. My experiments applied de-noising algorithms to complex images combining nonlinear filters based on order statistics methods in the wavelet domain, which demanded high computational power. The unavailability of HPC facilities imposed severe challenges for the research process required to achieve my proposed objectives. DE-NOISING COMPLEX IMAGESI graduated in 1999 from the School of Electrical Engineering of the Universidad Central "Marta Abreu" of Las Villas (UCLV) in Cuba. Since 2003, I have been linked to the Center for Studies on Electronics and Information Technologies (CEETI), where I did my PhD studies on de-noising complex images, meanwhile I served as head of the Telecommunications Department in the Electrical Engineering School. Upon receiving my PhD in 2007, I was nominated to and accepted the role of director of the UCLV Central ICT Department.

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Combined Wavelet and Nonlinear Filtering for MRI Phase Images

Cited by 2 publications

References 9 publications

A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps

A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps

Making Supercomputing Available to All Cuban Researchers

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