Multi-contrast magnetic resonance (MR) imaging is an advanced technology used in medical diagnosis, but the long acquisition process can lead to patient discomfort and limit its broader application. Shortening acquisition time by undersampling k-space data introduces noticeable aliasing artifacts. To address this, we propose a method that reconstructs multi-contrast MR images from zero-filled data by utilizing a fully-sampled auxiliary contrast MR image as a prior to learn an adjacency complementary graph.
View Article and Find Full Text PDFBackground: Recent Convolutional Neural Networks (CNNs) perform low-error reconstruction in fast Magnetic Resonance Imaging (MRI). Most of them convolve the image with kernels and successfully explore the local information. Nonetheless, the non-local image information, which is embedded among image patches relatively far from each other, may be lost due to the limitation of the receptive field of the convolution kernel.
View Article and Find Full Text PDFZhonghua Shi Yan He Lin Chuang Bing Du Xue Za Zhi
March 2003
Background: To test susceptibility of human liver cell line Hep G2 to HCV in vitro.
Methods: Hep G2 was cultivated with the serum from a chronic hepatitis C patient. After inoculation, plus and minus strand of HCV RNA, the expression of HCV NS3 antigen and the location of HCV RNA in cell and/or supernatant were examined by RT-PCR, immunohistochemistry and in situ hybridization, respectively.
Zhonghua Gan Zang Bing Za Zhi
December 2002
Objective: To investigate the pathogenesis of cytotoxic T cell (CTL) dysfunction in patients with HCV infection.
Methods: BALB/c mice were immunized by subcutaneous injection of polypeptides from HCV core region, and the CTL activity of mouse spleen cells was detected by the LDH release test. Two polypeptides which can enhance CTL function and two polypeptides which can inhibit CTL function were selected and cross-combined.