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ORCIDLiangliang Liu 0001
Person information
- affiliation: Central South University, School of Computer Science and Engineering, Changsha, China
Other persons with the same name
- Liangliang Liu — disambiguation page
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2020 – today
- 2024
[j21]Liangliang Liu
, Zhihong Liu, Jing Chang, Xue Xu:
A multi-modal extraction integrated model for neuropsychiatric disorders classification. Pattern Recognit. 155: 110646 (2024)- [j20]Liangliang Liu, Ying Wang, Pei Zhang, Hongbo Qiao, Tong Sun, Hui Zhang, Xue Xu, Hongcai Shang:
Collaborative Transfer Network for Multi-Classification of Breast Cancer Histopathological Images. IEEE J. Biomed. Health Informatics 28(1): 110-121 (2024) - [c11]Pei Zhang, Zhihong Liu, Liangliang Liu:
A Hybrid Feature Fusion Network for Predicting HER2 Status on H &E-Stained Histopathology Images. ISBRA (2) 2024: 38-46 - [c10]Xiangyu Li, Liangliang Liu:
Patch-Based Coupled Attention Network to Predict MSI Status in Colon Cancer. ISBRA (2) 2024: 132-139 - 2023
- [j19]Liangliang Liu, Pei Zhang, Gongbo Liang, Shufeng Xiong, Jianxin Wang, Guang Zheng:
A spatiotemporal correlation deep learning network for brain penumbra disease. Neurocomputing 520: 274-283 (2023) - [j18]Shufeng Xiong, Guipei Zhang, Vishwash Batra, Lei Xi, Lei Shi, Liangliang Liu:
TRIMOON: Two-Round Inconsistency-based Multi-modal fusion Network for fake news detection. Inf. Fusion 93: 150-158 (2023) - [j17]Liangliang Liu, Jing Chang, Gongbo Liang, Shufeng Xiong:
Simulated Quantum Mechanics-Based Joint Learning Network for Stroke Lesion Segmentation and TICI Grading. IEEE J. Biomed. Health Informatics 27(7): 3372-3383 (2023) - [j16]Liangliang Liu, Jing Chang, Pei Zhang, Hongbo Qiao, Shufeng Xiong:
SASG-GCN: Self-Attention Similarity Guided Graph Convolutional Network for Multi-Type Lower-Grade Glioma Classification. IEEE J. Biomed. Health Informatics 27(7): 3384-3395 (2023) - [j15]Liangliang Liu, Jing Chang, Zhihong Liu, Pei Zhang, Xue Xu, Hongcai Shang:
Hybrid Contextual Semantic Network for Accurate Segmentation and Detection of Small-Size Stroke Lesions From MRI. IEEE J. Biomed. Health Informatics 27(8): 4062-4073 (2023) - 2022
- [j14]Gongbo Liang, Halemane Ganesh, Dylan Steffe, Liangliang Liu, Nathan Jacobs, Jie Zhang:
Development of CNN models for the enteral feeding tube positioning assessment on a small scale data set. BMC Medical Imaging 22(1): 52 (2022) - [j13]Liangliang Liu, Ying Wang, Jing Chang, Pei Zhang, Gongbo Liang, Hui Zhang:
LLRHNet: Multiple Lesions Segmentation Using Local-Long Range Features. Frontiers Neuroinformatics 16: 859973 (2022) - [j12]Liangliang Liu, Yu-Ping Wang, Yi Wang, Pei Zhang, Shufeng Xiong:
An enhanced multi-modal brain graph network for classifying neuropsychiatric disorders. Medical Image Anal. 81: 102550 (2022) - [j11]Liangliang Liu, Shaojie Tang, Fang-Xiang Wu, Yu-Ping Wang, Jianxin Wang:
An Ensemble Hybrid Feature Selection Method for Neuropsychiatric Disorder Classification. IEEE ACM Trans. Comput. Biol. Bioinform. 19(3): 1459-1471 (2022) - [j10]Jianhong Cheng, Wei Zhao, Jin Liu, Xingzhi Xie, Shangjie Wu, Liangliang Liu, Hailin Yue, Junjian Li, Jianxin Wang, Jun Liu:
Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images. IEEE ACM Trans. Comput. Biol. Bioinform. 19(5): 2723-2736 (2022) - [c9]Yunni Qu, David Yan, Eric Xing, Fengbo Zheng, Jie Zhang, Liangliang Liu, Gongbo Liang:
Beware the Black-Box of Medical Image Generation: an Uncertainty Analysis by the Learned Feature Space. EMBC 2022: 3849-3853 - [c8]Eric Xing, Liangliang Liu, Xin Xing, Yunni Qu, Nathan Jacobs, Gongbo Liang:
Neural Network Decision-Making Criteria Consistency Analysis via Inputs Sensitivity. ICPR 2022: 2328-2334 - 2021
- [j9]Liangliang Liu, Jing Zhang, Jin-xiang Wang, Shufeng Xiong, Hui Zhang:
Co-optimization Learning Network for MRI Segmentation of Ischemic Penumbra Tissues. Frontiers Neuroinformatics 15: 782262 (2021) - [c7]Gongbo Liang, Xin Xing, Liangliang Liu, Yu Zhang, Qi Ying, Ai-Ling Lin, Nathan Jacobs:
Alzheimer's Disease Classification Using 2D Convolutional Neural Networks. EMBC 2021: 3008-3012 - [c6]Qi Ying, Xin Xing, Liangliang Liu, Ai-Ling Lin, Nathan Jacobs, Gongbo Liang:
Multi-Modal Data Analysis for Alzheimer's Disease Diagnosis: An Ensemble Model Using Imagery and Genetic Features. EMBC 2021: 3586-3591 - 2020
- [j8]Liangliang Liu, Shaowu Chen, Xiaofeng Zhu, Xing-Ming Zhao, Fang-Xiang Wu, Jianxin Wang:
Deep convolutional neural network for accurate segmentation and quantification of white matter hyperintensities. Neurocomputing 384: 231-242 (2020) - [j7]Liangliang Liu, Jianhong Cheng, Quan Quan, Fang-Xiang Wu, Yu-Ping Wang, Jianxin Wang:
A survey on U-shaped networks in medical image segmentations. Neurocomputing 409: 244-258 (2020) - [j6]Liangliang Liu, Lukasz A. Kurgan, Fang-Xiang Wu, Jianxin Wang:
Attention convolutional neural network for accurate segmentation and quantification of lesions in ischemic stroke disease. Medical Image Anal. 65: 101791 (2020) - [j5]Liangliang Liu, Shaowu Chen, Fuhao Zhang, Fang-Xiang Wu, Yi Pan, Jianxin Wang:
Deep convolutional neural network for automatically segmenting acute ischemic stroke lesion in multi-modality MRI. Neural Comput. Appl. 32(11): 6545-6558 (2020) - [j4]Liangliang Liu, Fang-Xiang Wu, Yu-Ping Wang, Jianxin Wang:
Multi-Receptive-Field CNN for Semantic Segmentation of Medical Images. IEEE J. Biomed. Health Informatics 24(11): 3215-3225 (2020) - [c5]Ning Liu, Liangliang Liu, Jianxin Wang:
Local Adaptive U-net for Medical Image Segmentation. BIBM 2020: 670-674
2010 – 2019
- 2019
- [j3]Ying Yu, Min Li, Liangliang Liu, Yaohang Li, Jianxin Wang:
Clinical big data and deep learning: Applications, challenges, and future outlooks. Big Data Min. Anal. 2(4): 288-305 (2019) - [j2]Liangliang Liu, Fang-Xiang Wu, Jianxin Wang:
Efficient multi-kernel DCNN with pixel dropout for stroke MRI segmentation. Neurocomputing 350: 117-127 (2019) - [j1]Ying Yu, Min Li, Liangliang Liu, Zhihui Fei, Fang-Xiang Wu, Jianxin Wang:
Automatic ICD code assignment of Chinese clinical notes based on multilayer attention BiRNN. J. Biomed. Informatics 91 (2019) - [c4]Ying Yu, Min Li, Liangliang Liu, Fang-Xiang Wu, Jianxin Wang:
Tentative diagnosis prediction via deep understanding of patient narratives. BIBM 2019: 1000-1003 - [c3]Jianhong Cheng, Jin Liu, Liangliang Liu, Yi Pan, Jianxin Wang:
Multi-level Glioma Segmentation using 3D U-Net Combined Attention Mechanism with Atrous Convolution. BIBM 2019: 1031-1036 - 2018
- [c2]Liangliang Liu, Shuai Yang, Li Meng, Min Li, Jianxin Wang:
Multi-scale Deep Convolutional Neural Network for Stroke Lesions Segmentation on CT Images. BrainLes@MICCAI (1) 2018: 283-291 - 2017
- [c1]Liangliang Liu, Jianxin Wang, Min Li, Fang-Xiang Wu, Hong-Dong Li, Ying Yu, Zhihui Fei:
An interpretable model for predicting side effects of analgesics for osteoarthritis. BIBM 2017: 861-864
Coauthor Index
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