| Liver CT sequence segmentation based with improved U-Net and graph cut Z Liu, YQ Song, VS Sheng, L Wang, R Jiang, X Zhang, D Yuan Expert Systems with Applications 126, 54-63, 2019 | 184 | 2019 |
| A survey on the interpretability of deep learning in medical diagnosis Q Teng, Z Liu, Y Song, K Han, Y Lu Multimedia Systems 28 (6), 2335-2355, 2022 | 101 | 2022 |
| DV-Net: Accurate liver vessel segmentation via dense connection model with D-BCE loss function J Su, Z Liu, J Zhang, VS Sheng, Y Song, Y Zhu, Y Liu Knowledge-Based Systems 232, 107471, 2021 | 74 | 2021 |
| Multi-atlas classification of autism spectrum disorder with hinge loss trained deep architectures: ABIDE I results TM Epalle, Y Song, Z Liu, H Lu Applied soft computing 107, 107375, 2021 | 61 | 2021 |
| An effective semi-supervised approach for liver CT image segmentation K Han, L Liu, Y Song, Y Liu, C Qiu, Y Tang, Q Teng, Z Liu IEEE Journal of Biomedical and Health Informatics 26 (8), 3999-4007, 2022 | 51 | 2022 |
| Deep semi-supervised learning for medical image segmentation: A review K Han, VS Sheng, Y Song, Y Liu, C Qiu, S Ma, Z Liu Expert Systems with Applications, 123052, 2024 | 48 | 2024 |
| Characterizing and predicting autism spectrum disorder by performing resting-state functional network community pattern analysis Y Song, TM Epalle, H Lu Frontiers in human neuroscience 13, 203, 2019 | 43 | 2019 |
| MRI and PET image fusion using the nonparametric density model and the theory of variable-weight Z Liu, Y Song, VS Sheng, C Xu, C Maere, K Xue, K Yang Computer Methods and Programs in Biomedicine 175, 73-82, 2019 | 33 | 2019 |
| Densely connected deep U-Net for abdominal multi-organ segmentation ZH Wang, Z Liu, YQ Song, Y Zhu 2019 IEEE International Conference on Image Processing (ICIP), 1415-1419, 2019 | 32 | 2019 |
| Advances on pancreas segmentation: a review X Yao, Y Song, Z Liu Multimedia Tools and Applications 79 (9), 6799-6821, 2020 | 31 | 2020 |
| RTUNet: Residual transformer UNet specifically for pancreas segmentation C Qiu, Z Liu, Y Song, J Yin, K Han, Y Zhu, Y Liu, VS Sheng Biomedical Signal Processing and Control 79, 104173, 2023 | 30 | 2023 |
| Automatic liver segmentation from abdominal CT volumes using improved convolution neural networks Z Liu, K Han, Z Wang, J Zhang, Y Song, X Yao, D Yuan, VS Sheng Multimedia Systems 27, 111-124, 2021 | 29 | 2021 |
| Pancreas Co-segmentation based on dynamic ROI extraction and VGGU-Net Z Liu, J Su, R Wang, R Jiang, YQ Song, D Zhang, Y Zhu, D Yuan, Q Gan, ... Expert Systems with Applications 192, 116444, 2022 | 26 | 2022 |
| A new clustering method of gene expression data based on multivariate Gaussian mixture models Z Liu, Y Song, C Xie, Z Tang Signal, Image and Video Processing 10, 359-368, 2016 | 24 | 2016 |
| CMFCUNet: cascaded multi-scale feature calibration UNet for pancreas segmentation C Qiu, Y Song, Z Liu, J Yin, K Han, Y Liu Multimedia Systems 29 (2), 871-886, 2023 | 21 | 2023 |
| HPM-Net: Hierarchical progressive multiscale network for liver vessel segmentation in CT images W Hao, J Zhang, J Su, Y Song, Z Liu, Y Liu, C Qiu, K Han Computer Methods and Programs in Biomedicine 224, 107003, 2022 | 21 | 2022 |
| Color image segmentation using nonparametric mixture models with multivariate orthogonal polynomials Z Liu, YQ Song, JM Chen, CH Xie, F Zhu Neural Computing and Applications 21, 801-811, 2012 | 21 | 2012 |
| Optimization of FireNet for liver lesion classification G Kashala Kabe, Y Song, Z Liu Electronics 9 (8), 1237, 2020 | 19 | 2020 |
| Multiple-kernel combination fuzzy clustering for community detection H Lu, Y Song, H Wei Soft Computing 24 (18), 14157-14165, 2020 | 15 | 2020 |
| Clustering gene expression data analysis using an improved EM algorithm based on multivariate elliptical contoured mixture models Z Liu, Y Song, C Xie, F Zhu, X Bao Optik 125 (21), 6388-6394, 2014 | 13 | 2014 |
