Li Qiang received his Ph.D. degree from Tianjin University, China, in 2003. He received his B. S. and M. S. from Taiyuan University of Technology, Taiyuan, China in 1997 and 2000, respectively. Now he is a professor with School of Microelectronics, Tianjin University. His research interests are focused on intelligent signal processing for musics and medical images. He has published more than 130 papers in IEEE Transaction on Multimedia, IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,  Expert System with Applications, Signal Processing-Imaging Communication, Cerebral Cortex, etc. 

• Machine learning and Deep learning in medical images (CT & MRI)
• Sound and music computation
• High-intensity focus ultrasound thermal therapy
• Hyperspectral image super-resolution reconstruction

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• [1]Liu, H., Huo, G., Li, Q., Guan, X., & Tseng, M. L. Multiscale lightweight 3D segmentation algorithm with attention mechanism: Brain tumor image segmentation[J]. Expert Systems with Applications, 2022. (SCI一区，IF=8.67)
• [2]Liang Q, Li Q, Nie W, et al. Unsupervised Cross-media Graph Convolutional Network for 2D Image-based 3D Model Retrieval[J]. IEEE Transactions on Multimedia, 2022. (SCI一区，IF=8.18)
• [3]Liang Q, Li Q, Nie W. LD-GAN: Learning perturbations for adversarial defense based on GAN structure[J]. Signal Processing: Image Communication, 2022. (SCI二区，IF=3.45)
• [4]Liang Q, Li Q, Nie W, et al. PAGN: perturbation adaption generation network for point cloud adversarial defense[J]. Multimedia Systems, 2022. (SCI四区，IF=2.60)
• [5]Younis A, Qiang L, Nyatega C O, et al. Brain Tumor Analysis Using Deep Learning and VGG-16 Ensembling Learning Approaches[J]. Applied Sciences-Basel, 2022. (SCI四区，IF=2.84)
• [6]Liang Q, Li Q, Nie W, et al. Principal views selection based on growing graph convolution network for multi-view 3D model recognition[J]. Applied Intelligence, 2022. (SCI二区，IF=5.02)
• [7]Zhou Y, Qiang Li, et al. Automated classification of mild cognitive impairment by machine learning with hippocampus-related white matter network[J]. Frontiers in aging neuroscience, 2022. (SCI二区，IF=5.70)
• [8]Guan X, Zhao H, Li Q. Estimation of playable piano fingering by pitch-difference fingering match model[J]. EURASIP Journal on Audio, Speech, and Music Processing, 2022. (SCI四区，IF=2.11)
• [9]Wang Z, Li Q, Nie K, et al. A delay cell with duty-cycle correction and parasitic compensation for large array indirect time-of-flight CMOS image sensors[J]. Microelectronics Journal, 2022. (SCI三区，IF=1.99)
• [10]Wu Y, Li Q, Wang I C. Adaptive Pneumonia Detection Algorithm based on Deep Learning[J]. Journal of Imaging Science & Technology, 2022. (SCI四区，IF=0.58)
• [11]Liang Q, Li Q, Zhang L, et al. MHFP: Multi-view based hierarchical fusion pooling method for 3D shape recognition[J]. Pattern Recognition Letters, 2021. (SCI三区，IF=4.76)
• [12]Liang Q, Li Q, Yang S. LP-GAN: Learning perturbations based on generative adversarial networks for point cloud adversarial attacks[J]. Image and Vision Computing, 2022. (SCI三区，IF=3.86)
• [13]Zhou Y, Qiang Li, et al. Hippocampus-and thalamus-related fibe-specific white matter reductions in mild cognitive impairment[J]. Cerebral Cortex, 2021. (SCI一区，IF=4.86)
• [14]Liang Q, Wang Y, Nie W, et al. MVCLN: multi-view convolutional LSTM network for cross-media 3D shape recognition[J]. IEEE Access, 2020. (SCI三区，IF=3.48)
• [15]Yang K, Li Q, Liu H L, et al. Frequency-domain CBE imaging for ultrasound localization of the HIFU focal spot: a feasibility study[J]. Scientific Reports, 2020. (SCI三区，IF=5)
• [16]Yan D, Li Q, Lin C W, et al. Clinical evaluation of duchenne muscular dystrophy severity using ultrasound small-window entropy imaging[J]. Entropy, 2020. (SCI三区，IF=2.74)
• [17]Fang F, Fang J, Li Q, et al. Ultrasound assessment of hepatic steatosis by using the double Nakagami distribution: a feasibility study[J]. Diagnostics, 2020. (SCI四区，IF=3.99)
• [18]Zhu C, Chang Y Z, Li Q. Accurate stereo matching based on weighted nonlocal aggregation for enhanced disparity refinement[J]. Journal of Electronic Imaging, 2018. (SCI四区，IF=0.83)
• [19]Zhang L, Li Q, Wang C Y, et al. Ultrasound single-phase CBE imaging for monitoring radiofrequency ablation[J]. International Journal of Hyperthermia, 2018. (SCI二区，IF=3.75)
• [20]Guan X, Du H, Li Q, et al. Combination of Window-Modulated Ultrasound Nakagami Imaging and Gaussian Approximation for Radiofrequency Ablation Monitoring: An In Vitro Study[J]. Journal of Medical and Biological Engineering, 2018. (SCI四区，IF=2.21)