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Some second order PDE-based image restoration models such as total variation (TV) minimization or ROF model of Rudin et al. (Physica D 60, 259–268, 1992) can easily give rise to staircase effect, which may produce undesirable blocky image. LOT model proposed by Laysker, Osher and Tai (IEEE Trans. Image Process. 13(10), 1345–1357, 2004) has alleviated the(More)
BACKGROUND Thyroid nodules (TNs) usually appearing in the general population have the potential possibility of malignant transformation and common problems of jugular oppression such as dyspnea and hoarseness. We performed this meta-analysis to evaluate the efficiency of radiofrequency ablation (RFA) for the treatment of benign TNs in accord with the(More)
BACKGROUND In recent years, neuroimaging has been increasingly used as an objective method for the diagnosis of Parkinson's disease (PD). Most previous studies were based on invasive imaging modalities or on a single modality which was not an ideal diagnostic tool. In this study, we developed a non-invasive technology intended for use in the diagnosis of(More)
PURPOSE Liver segmentation from computed tomography images is a challenging task owing to pixel intensity overlapping, ambiguous edges, and complex backgrounds. The authors address this problem with a novel active surface scheme, which minimizes an energy functional combining both edge- and region-based information. METHODS In this semiautomatic method,(More)
Segmentation of the liver from abdominal computed tomography (CT) images is an essential step in some computer-assisted clinical interventions, such as surgery planning for living donor liver transplant, radiotherapy and volume measurement. In this work, we develop a deep learning algorithm with graph cut refinement to automatically segment the liver in CT(More)
PURPOSE It is very important for calculation of clinical indices and diagnosis to detect thyroid nodules from ultrasound images. However, this task is a challenge mainly due to heterogeneous thyroid nodules with distinct components are similar to background in ultrasound images. In this study, we employ cascade deep convolutional neural networks (CNNs) to(More)
Image segmentation plays an important role in medical image analysis. The most widely used image segmentation algorithms, region-based methods that typically rely on the homogeneity of image intensities in the regions of interest, often fail to provide accurate segmentation results due to the existence of bias field, heavy noise and rich structures. In this(More)
PURPOSE To evaluate the accuracy of shear wave elastography (SWE) in the quantitative diagnosis of liver fibrosis severity. METHODS The published literatures were systematically retrieved from PubMed, Embase, Web of science and Scopus up to May 13th, 2016. Included studies reported the pooled sensitivity, specificity, positive and negative predictive(More)
Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous(More)