Publications by authors named "Chun-yu Chu"

Objective: The purpose of this paper is to increase the accuracy of human cardiac diffusion tensor (DT) estimation in diffusion magnetic resonance imaging (dMRI) with a few diffusion gradient directions.

Methods: A structure prior constrained (SPC) method is proposed. The method consists in introducing two regularizers in the conventional nonlinear least squares estimator.

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Background: Non-monoexponential diffusion models are being used increasingly for the characterization and curative effect evaluation of hepatocellular carcinoma (HCC). But the fitting quality of the models and the repeatability of their parameters have not been assessed for HCC.

Purpose: To evaluate kurtosis, stretched exponential, and statistical models for diffusion-weighted imaging (DWI) of HCC, using b-values up to 2000 s/mm , in terms of fitting quality and repeatability.

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Purpose: To distinguish hepatocellular carcinoma (HCC) from other types of hepatic lesions with the adaptive multi-exponential IVIM model.

Methods: 94 hepatic focal lesions, including 38 HCC, 16 metastasis, 12 focal nodular hyperplasia, 13 cholangiocarcinoma, and 15 hemangioma, were examined in this study. Diffusion-weighted images were acquired with 13 b values (b = 0, 3, …, 500 s/mm) to measure the adaptive multi-exponential IVIM parameters, namely, pure diffusion coefficient (D), diffusion fraction (f), pseudo-diffusion coefficient (D*) and perfusion-related diffusion fraction (f) of the ith perfusion component.

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Orientation distribution functions (ODFs) are widely used to resolve fiber crossing problems in high angular resolution diffusion imaging (HARDI). The characteristics of the ODFs are often assessed using a visual criterion, although the use of objective criteria is also reported, which are directly borrowed from classic signal and image processing theory because they are intuitive and simple to compute. However, they are not always pertinent for the characterization of ODFs.

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Diffusion tensor imaging and high angular resolution diffusion imaging are often used to analyze the fiber complexity of tissues. In these imaging techniques, the most commonly calculated metric is anisotropy, such as fractional anisotropy (FA), generalized anisotropy (GA), and generalized fractional anisotropy (GFA). The basic idea underlying these metrics is to compute the deviation from free or spherical diffusion.

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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 local fiber orientations.

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