Deep Learning

  • Vanderbilt University

    Field-of-view extension for brain diffusion MRI via deep generative models

    Gao, Chenyu, Bao, Shunxing, Kim, Michael E., Newlin, Nancy R., Kanakaraj, Praitayini, Yao, Tianyuan, Rudravaram, Gaurav, Huo, Yuankai, Moyer, Daniel, Schilling, Kurt, Kukull, Walter A., & Toga, Arthur W. (2024). Field-of-view extension for brain diffusion MRI via deep generative models. Journal of Medical Imaging, 11(4), 044008. https://doi.org/10.1117/1.JMI.11.4.044008… Read More

    Sep. 22, 2024

  • Vanderbilt University

    Time-Series Few Shot Anomaly Detection for HVAC Systems

    Huang, Yuxin, Coursey, Austin, Quinones-Grueiro, Marcos, & Biswas, Gautam. (2024). Time-series few shot anomaly detection for HVAC systems. In Proceedings of the 12th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS 2024), Ferrara, Italy, June 4-7, 2024, Volume 58, Issue 4, Pages 426-431. Read More

    Sep. 22, 2024

  • Vanderbilt University

    Genetic Improvement for DNN Security

    Baxter, Hunter, Huang, Yu, & Leach, Kevin. (2024). Genetic improvement for DNN security. In Proceedings of the 13th International Genetic Improvement Workshop (GI@ICSE 2024), Lisbon, Portugal, April 16, 2024, Pages 11-12. https://doi.org/10.1145/3643692.3648261 This study explores a novel application of Genetic Improvement (GI) in enhancing the security of Deep Neural Networks… Read More

    Sep. 22, 2024

  • Vanderbilt University

    Mitigating Over-Saturated Fluorescence Images Through a Semi-Supervised Generative Adversarial Network

    Bao, Shunxing, Guo, Junlin, Lee, Ho Hin, Deng, Ruining, Cui, Can, Remedios, Lucas W., Liu, Quan, Yang, Qi, Xu, Kaiwen, Yu, Xin, Li, Jia, & Li, Yike. (2024). Mitigating over-saturated fluorescence images through a semi-supervised generative adversarial network. In Proceedings of the 21st IEEE International Symposium on Biomedical Imaging (ISBI… Read More

    Sep. 22, 2024

  • Vanderbilt University

    SE(3)-Equivariant and Noise-Invariant 3D Rigid Motion Tracking in Brain MRI

    Benjamin Billot, Neel Dey, Daniel Moyer, Malte Hoffmann, Esra Abaci Turk, Borjan Gagoski, P. Ellen Grant, & Polina Golland. (2024). SE(3)-Equivariant and Noise-Invariant 3D Rigid Motion Tracking in Brain MRI. IEEE Transactions on Medical Imaging, 1-12. https://doi.org/10.1109/TMI.2024.3411989 Tracking movement accurately in medical imaging, like MRI scans… Read More

    Jul. 21, 2024

  • Vanderbilt University

    Deep conditional generative model for longitudinal single-slice abdominal computed tomography harmonization

    Xin Yu, Qi Yang, Yucheng Tang, Riqiang Gao, Shunxing Bao, Leon Y. Cai, Ho Hin Lee, Yuankai Huo, Ann Zenobia Moore, Luigi Ferrucci, and Bennett A. Landman. “Deep Conditional Generative Model for Longitudinal Single-slice Abdominal Computed Tomography Harmonization.” Journal of Medical Imaging (Bellingham), vol. 11, no. 2, 024008, March… Read More

    Jun. 20, 2024

  • Vanderbilt University

    Evaluation of Mean Shift, ComBat, and CycleGAN for Harmonizing Brain Connectivity Matrices Across Sites

    Hanliang Xu, Nancy R. Newlin, Michael E. Kim, Chenyu Gao, Praitayini Kanakaraj, Aravind R. Krishnan, Lucas W. Remedios, Nazirah Mohd Khairi, Kimberly Pechman, Derek Archer, Timothy J. Hohman, Angela L. Jefferson, Ivana Išgum, Yuankai Huo, Daniel Moyer, Kurt G. Schilling, and Bennett A. Landman. “Evaluation of Mean Shift, ComBat,… Read More

    Jun. 20, 2024

  • Vanderbilt University

    Learning-based Free-Water Correction using Single-shell Diffusion MRI

    Tianyuan Yao, Derek B. Archer, Praitayini Kanakaraj, Nancy Newlin, Shunxing Bao, Daniel Moyer, Kurt Schilling, Bennett A. Landman, and Yuankai Huo. “Learning-based Free-water Correction Using Single-shell Diffusion MRI.” Proceedings of SPIE Medical Imaging 2024: Image Processing, vol. 12926, 1292607, 2024, San Diego, California Diffusion magnetic resonance imaging (dMRI) enables… Read More

    Jun. 20, 2024

  • Vanderbilt University

    Leverage Weakly Annotation to Pixel-wise Annotation via Zero-shot Segment Anything Model for Molecular-empowered Learning

    Xueyuan Li, Ruining Deng, Yucheng Tang, Shunxing Bao, Haichun Yang, and Yuankai Huo. “Leverage Weekly Annotation to Pixel-wise Annotation via Zero-shot Segment Anything Model for Molecular-empowered Learning.” Proceedings of SPIE Medical Imaging 2024: Digital and Computational Pathology, vol. 12933, 129330K, 2024, San Diego, California Precise identification of multiple cell… Read More

    Jun. 20, 2024

  • Vanderbilt University

    Meta-optic accelerators for object classifiers

    Hanyu Zheng, Quan Liu, You Zhou, Ivan I. Kravchenko, Yuankai Huo, and Jason Valentine. “Meta-optic Accelerators for Object Classifiers.” Science Advances, vol. 8, no. 30, 27 July 2022. Rapid advances in deep learning have led to significant transformations across various fields, including medical image analysis and autonomous systems. These… Read More

    Jun. 20, 2024