Fucang Jia

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Neuronal recording and neuroimaging studies have shown that the primary motor area (M1) not only participates in motor execution, but is also engaged during movement preparation. The purpose of the present study was to map the distribution of the preparation- and execution-related activity within the contralateral M1 using functional magnetic resonance(More)
Efficient visualization of vascular structures is essential for therapy planning and medical education. Existing techniques achieve high-quality visualization of vascular surfaces at the cost of low rendering speed and large size of resulting surface. In this paper, we present an approach for visualizing vascular structures by exploiting the local curvature(More)
This paper describes a preprocessing mask technique based statistical mixture components segmentation method for extracting blood vessels from brain magnetic resonance angiography (MRA) dataset. The voxels whose intensity is high in the dataset belong to blood vessels or brain skulls, which may bias the adjustment of the blood vessels. Maximum intensity(More)
BACKGROUND The effective geometric modeling of vascular structures is crucial for diagnosis, therapy planning and medical education. These applications require good balance with respect to surface smoothness, surface accuracy, triangle quality and surface size. METHODS Our method first extracts the vascular boundary voxels from the segmentation result,(More)
In this paper, an automatic and robust coarse-to-fine liver image segmentation method is proposed. Multiple prior knowledge models are built to implement liver localization and seg-mentation: voxel-based AdaBoost classifier is trained to localize liver position robustly, shape and appearance models are constructed to fit liver shape and appearance models to(More)
Cerebral glioma is one of the most aggressive space-occupying diseases, which will exhibit midline shift (MLS) due to mass effect. MLS has been used as an important feature for evaluating the pathological severity and patients’ survival possibility. Automatic quantification of MLS is challenging due to deformation, complex shape and complex grayscale(More)
In recent years, research on human functional brain imaging using resting-state fMRI techniques has been increasingly prevalent. The term “default mode” was proposed to describe a baseline or default state of the brain during rest. Recent studies suggested that the default mode network (DMN) is comprised of two functionally distinct subsystems: a(More)
An approach to segment macular layer thicknesses from spectral domain optical coherence tomography has been proposed. The main contribution is to decrease computational costs while maintaining high accuracy via exploring Kalman filtering, customized active contour, and curve smoothing. Validation on 21 normal volumes shows that 8 layer boundaries could be(More)
An adaptively regularized kernel-based fuzzy C-means clustering framework is proposed for segmentation of brain magnetic resonance images. The framework can be in the form of three algorithms for the local average grayscale being replaced by the grayscale of the average filter, median filter, and devised weighted images, respectively. The algorithms employ(More)