Lei Zhang

Assistant Professor

Name

Contact Info

Phone:
410-704-2507
Office:
YR-445
Email:
leizhang@towson.edu
Hours:
Mon. / Wed., 10:30 a.m. - 12 p.m., or by appointment.

Education

Ph.D., Computer Applied Technology, Harbin Institute of Technology, 2013

M.E., Software Engineering, Harbin Institute of Technology, 2008

B.E., Computer Science and Technology, Harbin University of Commerce, 2003

Areas of Expertise

Medical image analysis

Machine learning

Computer vision

Journal Publications

  • Zhang X, Liu J, Xian X, Chen B, Li D, Yang F, Zhang L. PSVT: Pyramid Shifted Window based Vision Transformer for cardiac image segmentation. Biomedical Signal Processing and Control. 2025 Apr 1; 102:107339.
  • Cheema MN, Zhang L, Nazir A, Li Y, Detre JA, Wang Z. Transformer-based arterial spin labeling perfusion MRI denoising. The Visual Computer. 2025 Jul 3:1-1.
  • Zhang L, Wang X, Rawson M, Balan R, Herskovits EH, Melhem ER, Chang L, Wang Z, Ernst T. Motion Correction for Brain MRI Using Deep Learning and a Novel Hybrid Loss Function. Algorithms. 2024 May 15;17(5):215.
  • Zhang L, LaBelle W, Unberath M, Chen H, Hu J, Li G, Dreizin D. A vendor-agnostic, PACS integrated, and DICOM-compatible software-server pipeline for testing segmentation algorithms within the clinical radiology workflow. Frontiers in Medicine. 2023.
  • Dreizin D, Zhang L, Sarkar N, Bodanapally UK, Li G, Hu J, Chen H, Khedr M, Khetan U, Campbell P, Unberath M. Accelerating voxelwise annotation of cross-sectional imaging through AI collaborative labeling with quality assurance and bias mitigation. Frontiers in Radiology. 2023 Jul 11; 3:1202412.
  • Zhang L*, Xie D*, Li Y, Camargo A, Song D, Lu T, Jeudy J, Dreizin D, Melhem E, Wang Z. Improving Sensitivity of Arterial Spin Labeling Perfusion MRI in Alzheimer's Disease Using Transfer Learning of Deep Learning-Based ASL Denoising. Journal of Magnetic Resonance Imaging. 2021 Nov. (Co-first author)
  • Zhang L, Mohamed A, Chai R, Zheng B, Wu S. Deep learning method for whole-breast segmentation in diffusion-weighted breast magnetic resonance images. Journal of Magnetic Resonance Imaging. 2020 Feb;51(2):635-43.
  • Hao D, Zhang L, Mohamed A, Wu S. Inaccurate labels in weakly supervised deep learning: automatic identification and correction and their impact on classification performance. Journal of Biomedical and Health Informatics. 2020 Feb 17.
  • Yang F*, Zhang L*, Yu S, Prokhorov D, Mei X, Ling H. Feature pyramid and hierarchical boosting network for pavement crack detection. IEEE Transactions on Intelligent Transportation Systems. 2019 Apr 22;21(4):1525-35. (Co-first author)

Conference Publications and Presentations

  • Zhang L, Herskovits EH, Melhem ER, Chang L, Wang Z, Ernst T. Reducing motion artifacts in brain MRI using vision transformers and self-supervised learning. In 2024 IEEE International Conference on Image Processing (ICIP) 2024 Oct 27 (pp. 3165-3171). IEEE.
  • Zhang L, Xie D, Wang Z. Doubling Temporal Resolution Using Multiscale-Wide-Inference & Ensemble Learning-Based Deep Neural Networks. International Society for Magnetic Resonance in Medicine Workshop on Perfusion MRI From Head to Toe 2022.
  • Zhang L, Wang X, Rawson M, Balan R, Herskovits E, Chang L, Wang Z, Ernst T. Motion correction in MRI with large movements using deep learning and a novel hybrid loss function. International Society for Magnetic Resonance in Medicine 2021 Annual Meeting.
  • Zhang L, Arefan D, Guo Y, Wu S. Fully automated tumor localization and segmentation in breast DCE-MRI using deep learning and kinetic prior. In Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications. International Society for Optics and Photonics.
  • Zhang L, Luo Z, Chai R, Arefan D, Sumkin J, Wu S. Deep-learning method for tumor segmentation in breast DCE-MRI. In Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications 2019 Mar 15 (Vol. 10954, p. 109540F). International Society for Optics and Photonics.
  • Zhang L, Chai R, Mohamed AA, Zheng B, Luo Z, Wu S. Automated deep-learning method for whole-breast segmentation in diffusion-weighted breast MRI. In Medical Imaging 2019: Computer-Aided Diagnosis 2019 Mar 13 (Vol. 10950, p. 109502R). International Society for Optics and Photonics.
  • Zhang L, Chen X, Liang Y, Mohamed A, Tong Y, Shen K, Wu S. Quantitative MRI background parenchymal enhancement and contralateral breast cancer risk. Radiological Society of North America 2018 Scientific Assembly and Annual Meeting.
  • Yao Y, Wu X, Zhang L, Shan S, Zuo W. Joint representation and truncated inference learning for correlation filter based tracking. In Proceedings of the European Conference on Computer Vision (ECCV) 2018 (pp. 552-567).
  • Zhou Z, Shin J, Zhang L, Gurudu S, Gotway M, Liang J. Fine-tuning convolutional neural networks for biomedical image analysis: actively and incrementally. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 2017 (pp. 7340-7351).
  • Zhang L, Zhou Z, Siddiki H, Madiraju NS, Baffy N, Franco D, Ramirez FC, Gurudu SR, Liang J. Gastroenterology fellow level performance on colonoscopy frame classification with deep neural networks. World Congress of Gastroenterology at American College of Gastroenterology 2017 Meeting.
  • Zhang L, Yang F, Zhang YD, Zhu YJ. Road crack detection using deep convolutional neural networks. In 2016 IEEE International Conference on Image Processing (ICIP) 2016 Sep 25 (pp. 3708-3712). IEEE.