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Description: MRI Susceptibility Weighted Imaging discusses the promising new MRI technique called Susceptibility Weighted Imaging (SWI), a powerful tool for the diagnosis and treatment of acute stroke, allowing earlier detection of acute stroke hemorrhage and easier detection of microbleeds in acute ischemia. The book is edited by the originators of SWI and(More)
A dual-echo pulse sequence for simultaneous acquisition of MR angiography and venography (MRAV) is developed. Data acquisition of the second echo for susceptibility-weighted imaging-based MR venography is added to the conventional three-dimensional (3D) time-of-flight (TOF) MRA pulse sequence. Using this dual-echo acquisition approach, the venography data(More)
PURPOSE To reduce the off-resonance artifact in susceptibility-weighted imaging (SWI)-based MR venography (MRV) in the brain regions with severe field inhomogeneity and to reduce the signal loss in the minimum-intensity projection (mIP) display of the 3D MRV. MATERIALS AND METHODS A novel postprocessing approach was presented to map the local field(More)
PURPOSE To improve the visibility of veins in susceptibility-weighted imaging (SWI) using a multi-gradient echo acquisition. MATERIALS AND METHODS A three-dimensional multi-echo gradient-echo pulse sequence was developed for simultaneous acquisition of MR angiography and multiple volumes of MR venography (MRV) of the brain. The first echo was acquired for(More)
Conventional susceptibility-weighted imaging (SWI) uses both phase and magnitude data for the enhancement of venous vasculature and, thus, is subject to signal loss in regions with severe field inhomogeneity and in the peripheral regions of the brain in the minimum-intensity projection. The purpose of this study is to enhance the visibility of the venous(More)
PURPOSE To develop a robust algorithm for tissue-air segmentation in magnetic resonance imaging (MRI) using the statistics of phase and magnitude of the images. MATERIALS AND METHODS A multivariate measure based on the statistics of phase and magnitude was constructed for tissue-air volume segmentation. The standard deviation of first-order phase(More)
Compressed Sensing (CS) increases the speed of MRI by reducing the sampling data. k-t FOCUSS is an effective CS algorithm for image reconstruction in dynamic MRI. In this method, in order to further improve its performance, a predictive frame is first obtained using the Motion Estimation (ME) and Motion Compensation (MC) algorithms, and the quality of(More)
Motion prediction algorithms are often used in dynamic magnetic resonance imaging to improve the compressed sensing based reconstruction. Previously, the difference calculation (DC) between the current frame (to be reconstructed) and the estimated frame was used as sparse residual signals. In order to obtain sparser signal, an improved Motion Estimation(More)
Based on a scattering center parametric model derived from the geometric theory of diffraction, main characteristic scattering center Fisher optimal discriminator is presented in this paper for the problem of multi-class ground targets. All aspect main characteristic scattering center recognition model and target outline characteristic curve recognition(More)
Susceptibility weighted imaging (SWI) in magnetic resonance imaging (MRI) has shown great merits in diagnosing brain diseases related to venous vasculature. A relatively long echo time (TE) is typically used for optimal venous contrast. This often leads to a long scan time for high resolution SWI, and can hamper routine clinical applications. Recently,(More)