Liangliang Liu

According to our database, Liangliang Liu authored at least 34 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

H-Net: Heterogeneous Neural Network for Multi-Classification of Neuropsychiatric Disorders.

Liangliang Liu, Jinpu Xie, Jing Chang, Zhihong Liu, Tong Sun, Hongbo Qiao, Gongbo Liang, Wei Guo

IEEE J. Biomed. Health Informatics, September, 2024

GVC-YOLO: A Lightweight Real-Time Detection Method for Cotton Aphid-Damaged Leaves Based on Edge Computing.

Zhenyu Zhang, Yunfan Yang, Xin Xu, Liangliang Liu, Jibo Yue, Ruifeng Ding, Yanhui Lu, Jie Liu, Hongbo Qiao

Remote. Sens., August, 2024

Collaborative Transfer Network for Multi-Classification of Breast Cancer Histopathological Images.

Liangliang Liu, Ying Wang, Pei Zhang, Hongbo Qiao, Tong Sun, Hui Zhang, Xue Xu, Hongcai Shang

IEEE J. Biomed. Health Informatics, January, 2024

A multi-modal extraction integrated model for neuropsychiatric disorders classification.

Liangliang Liu, Zhihong Liu, Jing Chang, Xue Xu

Pattern Recognit., 2024

A Hybrid Feature Fusion Network for Predicting HER2 Status on H &E-Stained Histopathology Images.

Pei Zhang, Zhihong Liu, Liangliang Liu

Proceedings of the Bioinformatics Research and Applications - 20th International Symposium, 2024

Patch-Based Coupled Attention Network to Predict MSI Status in Colon Cancer.

Xiangyu Li, Liangliang Liu

Proceedings of the Bioinformatics Research and Applications - 20th International Symposium, 2024

2023

Hybrid Contextual Semantic Network for Accurate Segmentation and Detection of Small-Size Stroke Lesions From MRI.

Liangliang Liu, Jing Chang, Zhihong Liu, Pei Zhang, Xue Xu, Hongcai Shang

IEEE J. Biomed. Health Informatics, August, 2023

SASG-GCN: Self-Attention Similarity Guided Graph Convolutional Network for Multi-Type Lower-Grade Glioma Classification.

Liangliang Liu, Jing Chang, Pei Zhang, Hongbo Qiao, Shufeng Xiong

IEEE J. Biomed. Health Informatics, July, 2023

Simulated Quantum Mechanics-Based Joint Learning Network for Stroke Lesion Segmentation and TICI Grading.

Liangliang Liu, Jing Chang, Gongbo Liang, Shufeng Xiong

IEEE J. Biomed. Health Informatics, July, 2023

TRIMOON: Two-Round Inconsistency-based Multi-modal fusion Network for fake news detection.

Shufeng Xiong, Guipei Zhang, Vishwash Batra, Lei Xi, Lei Shi, Liangliang Liu

Inf. Fusion, May, 2023

A spatiotemporal correlation deep learning network for brain penumbra disease.

Liangliang Liu, Pei Zhang, Gongbo Liang, Shufeng Xiong, Jianxin Wang, Guang Zheng

Neurocomputing, 2023

2022

An Ensemble Hybrid Feature Selection Method for Neuropsychiatric Disorder Classification.

Liangliang Liu, Shaojie Tang, Fang-Xiang Wu, Yu-Ping Wang, Jianxin Wang

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images.

Jianhong Cheng, Wei Zhao, Jin Liu, Xingzhi Xie, Shangjie Wu, Liangliang Liu, Hailin Yue, Junjian Li, Jianxin Wang, Jun Liu

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

An enhanced multi-modal brain graph network for classifying neuropsychiatric disorders.

Liangliang Liu, Yu-Ping Wang, Yi Wang, Pei Zhang, Shufeng Xiong

Medical Image Anal., 2022

LLRHNet: Multiple Lesions Segmentation Using Local-Long Range Features.

Liangliang Liu, Ying Wang, Jing Chang, Pei Zhang, Gongbo Liang, Hui Zhang

Frontiers Neuroinformatics, 2022

Development of CNN models for the enteral feeding tube positioning assessment on a small scale data set.

Gongbo Liang, Halemane Ganesh, Dylan Steffe, Liangliang Liu, Nathan Jacobs, Jie Zhang

BMC Medical Imaging, 2022

Neural Network Decision-Making Criteria Consistency Analysis via Inputs Sensitivity.

Eric Xing, Liangliang Liu, Xin Xing, Yunni Qu, Nathan Jacobs, Gongbo Liang

Proceedings of the 26th International Conference on Pattern Recognition, 2022

Beware the Black-Box of Medical Image Generation: an Uncertainty Analysis by the Learned Feature Space.

Yunni Qu, David Yan, Eric Xing, Fengbo Zheng, Jie Zhang, Liangliang Liu, Gongbo Liang

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021

Co-optimization Learning Network for MRI Segmentation of Ischemic Penumbra Tissues.

Liangliang Liu, Jing Zhang, Jin-xiang Wang, Shufeng Xiong, Hui Zhang

Frontiers Neuroinformatics, 2021

Multi-Modal Data Analysis for Alzheimer's Disease Diagnosis: An Ensemble Model Using Imagery and Genetic Features.

Qi Ying, Xin Xing, Liangliang Liu, Ai-Ling Lin, Nathan Jacobs, Gongbo Liang

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Alzheimer's Disease Classification Using 2D Convolutional Neural Networks.

Gongbo Liang, Xin Xing, Liangliang Liu, Yu Zhang, Qi Ying, Ai-Ling Lin, Nathan Jacobs

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

2020

Multi-Receptive-Field CNN for Semantic Segmentation of Medical Images.

Liangliang Liu, Fang-Xiang Wu, Yu-Ping Wang, Jianxin Wang

IEEE J. Biomed. Health Informatics, 2020

Deep convolutional neural network for automatically segmenting acute ischemic stroke lesion in multi-modality MRI.

Liangliang Liu, Shaowu Chen, Fuhao Zhang, Fang-Xiang Wu, Yi Pan, Jianxin Wang

Neural Comput. Appl., 2020

Attention convolutional neural network for accurate segmentation and quantification of lesions in ischemic stroke disease.

Liangliang Liu, Lukasz A. Kurgan, Fang-Xiang Wu, Jianxin Wang

Medical Image Anal., 2020

Deep convolutional neural network for accurate segmentation and quantification of white matter hyperintensities.

Liangliang Liu, Shaowu Chen, Xiaofeng Zhu, Xing-Ming Zhao, Fang-Xiang Wu, Jianxin Wang

Neurocomputing, 2020

A survey on U-shaped networks in medical image segmentations.

Liangliang Liu, Jianhong Cheng, Quan Quan, Fang-Xiang Wu, Yu-Ping Wang, Jianxin Wang

Neurocomputing, 2020

Local Adaptive U-net for Medical Image Segmentation.

Ning Liu, Liangliang Liu, Jianxin Wang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019

Automatic ICD code assignment of Chinese clinical notes based on multilayer attention BiRNN.

Ying Yu, Min Li, Liangliang Liu, Zhihui Fei, Fang-Xiang Wu, Jianxin Wang

J. Biomed. Informatics, 2019

Efficient multi-kernel DCNN with pixel dropout for stroke MRI segmentation.

Liangliang Liu, Fang-Xiang Wu, Jianxin Wang

Neurocomputing, 2019

Clinical big data and deep learning: Applications, challenges, and future outlooks.

Ying Yu, Min Li, Liangliang Liu, Yaohang Li, Jianxin Wang

Big Data Min. Anal., 2019

Tentative diagnosis prediction via deep understanding of patient narratives.

Ying Yu, Min Li, Liangliang Liu, Fang-Xiang Wu, Jianxin Wang

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Multi-level Glioma Segmentation using 3D U-Net Combined Attention Mechanism with Atrous Convolution.

Jianhong Cheng, Jin Liu, Liangliang Liu, Yi Pan, Jianxin Wang

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018

Multi-scale Deep Convolutional Neural Network for Stroke Lesions Segmentation on CT Images.

Liangliang Liu, Shuai Yang, Li Meng, Min Li, Jianxin Wang

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

2017

An interpretable model for predicting side effects of analgesics for osteoarthritis.

Liangliang Liu, Jianxin Wang, Min Li, Fang-Xiang Wu, Hong-Dong Li, Ying Yu, Zhihui Fei

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017