Yan-Li Zhang

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Although promising for studying the microstructure of in vivo tissues, the performance and the potentiality of diffusion tensor magnetic resonance imaging are hampered by the presence of high-level noise in diffusion weighted (DW) images. This paper proposes a novel smoothing approach, called the nonstationarity adaptive filtering, which estimates the(More)
A main source of problem in human cardiac diffusion tensor magnetic resonance imaging (DT-MRI) is the presence of high noise that buries useful information such as edges, details, and even whole objects. We propose a new enhancement approach based on the combined use of non-stationarity degree (NSD) notion and amoebas algorithm. The method consists of first(More)
PURPOSE A generalized intravoxel incoherent motion (IVIM) model, called the GIVIM, was proposed to better account for complex perfusion present in the tissues having various vessels and flow regimes, such as the liver. THEORY AND METHODS The notions of continuous pseudodiffusion variable as well as perfusion fraction density function were introduced to(More)
Fiber tractography techniques in diffusion magnetic resonance imaging have become a primary tool for studying the fiber architecture of biological tissues both noninvasively and in vivo. Streamline tracking, as a simple and efficient tractography technique, is widely used to reconstruct fiber pathways. It is however very sensitive to noisy estimation of(More)
In diffusion magnetic resonance imaging (dMRI), the accuracy of fiber tracking and analysis depends directly on that of intravoxel fiber architecture reconstruction. Several methods have been proposed that estimate intravoxel fiber architecture using low angular resolution acquisitions owing to their shorter acquisition time and relatively low bvalues. But(More)
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