Ohio University

Learning & Intelligent Systems Lab

Medical Image Analysis

Brain Analysis

Brain Analysis (sponspored by Univ. of Kentucky, NIH)

  • Yue, Y., Baltes, M., Abuhajar, N., ... & Liu, J. (2023). Spiking neural networks fine-tuning for brain image segmentation. Frontiers in Neuroscience, 17. [pdf]

  • Shi et. al, Nonlinear feature transformation and deep fusion for Alzheimer's Disease staging analysis. Pattern Recognition, 2017 [link] [pdf]

    • Shi, B., Liu, J. (2018). Nonlinear Metric Learning for kNN and SVMs through Geometric Transformations. Neurocomputing [pdf]

    • Zhang, P., et al, (2017). Nonlinear Feature Space Transformation to Improve the Prediction of MCI to AD Conversion. MICCAI 2017 [pdf ]

    • Chen et. al, Hippocampus Segmentation through Multi-view Ensemble ConvNets, ISBI 2017 [link] [pdf]
      • Hobbs et. al, Quad-mesh based radial distance biomarkers for Alzheimer's Disease, ISBI 2016: [link] [pdf]
        • Chen et. al, Accurate and Consistent Hippocampus Segmentation Through Convolutional LSTM and View Ensemble, MIML 2017 [link] [pdf]

          • Wang et. al, Ensemble of mUlti-sized FCNs to Improve White Matter Lesion Segmentation, MLMI 2018 [link] [pdf]

            • Digitial Pathology

            Digital Pathology (sponsored by Charles River Labs)



          • Wang et. al, Residual Pyramid FCN for Robust Follicle Segmentation. ISBI 2019 [link] [pdf]

            • Zhewei Wang, Fully Convoultional Networks (FCNs) for Medical Image Segmentation, December, 2020, [OhioLINK]

              • Autonomous Robots and Drones

              Deep Reinforcement Learning (DRL)

              Reinforcement Learning (sponsored by OHIO)


            • Song, S., Saunders, K., Yue, Y., & Liu, J. (2022). Smooth Trajectory Collision Avoidance through Deep Reinforcement Learning. IEEE ICMLA'22. [pdf]
            • Song et al, Vision-based Collision Avoidance through Deep Reinforcement Learning, IEEE NAECON 2021 [pdf]

              • ML/AI for Airport Runway Monitoring

              Smart Airport

              Airport Runway Monitoring (sponsored by FAA)


            • Song, S., Qin, X., Brengman, J., Bartone, C., Liu, J. (2023). Holistic FOD Detection Via Surface Map and Yolo Networks. 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP); 1-6. [[link]]

            • Airport runway/taxiway pavement condition prediction.

              • Spiking Neural Networks

              Neuromorphic Computing

              Spiking Neural Nets (sponsored by OHIO and USAF STTR program)


            • Yue, Y., Baltes, M., Abuhajar, N., ... & Liu, J. (2023). Spiking neural networks fine-tuning for brain image segmentation. Frontiers in Neuroscience, 17. [pdf]
            • Baltes, M., Abujahar, Yue, Y., T., Smith, C. D., Liu, J. (2023). Joint ANN-SNN Co-training for Object Localization and Image Segmentation. IEEE ICASSP'23 [pdf]
            • Marc Baltes, Hybrid ANN-SNN co-Training for Object Localization and Image Segmentation, M.S. thesis, April 2023. [OhioLINK]
            • Yue, Y., Baltes, M., Abujahar, N., Sun, T., Smith, C. D., Bihl, T., & Liu, J. (2023). Hybrid Spiking Neural Network Fine-tuning for Hippocampus Segmentation. IEEE ISBI'23 [pdf]
            • Marc Batles, Hybrid ANN-SNN Co-Training for Object Localization and Image Segmentation, M.S. thesis, April 2023. [OhioLINK]
            • Colton C. Smith, The Evaluation of Current Spiking Neural Network Conversion Methods in Radar Data, M.S. thesis, Aug. 2021. [OhioLINK]

              • Speech and NLP

              Speech Enhancement

              Speech Enhancement (sponsored by OHIO)


            • Sun et al, Boosting the Intelligibility of Speech Enhancement Networks Through Self-Supervised Representations), ICAML'21, [link] [pdf]

            • Sun et al, Individualized Conditioning and Negative Distances for Speaker Separation. IEEE ICMLA'22 [pdf]

            • Abuhajar et al, Individualized Conditioning and Negative Distances for Speaker Separation. IEEE ICMLA'22 [pdf]

            • Gong et al., Dilated FCN: listening longer to hear better, WASPAA’19 [link] [pdf]

                • Radar Signal Processing

                Emitter Detection

                Emitter Detection (sponsored by USAF STTR Program)


              • Colton C. Smith, The Evaluation of Current Spiking Neural Network Conversion Methods in Radar Data, M.S. thesis, Aug. 2021. [OhioLINK]

              • McGee et. al, Network Fusion for Radar Emitter Detection, NAECON 2021 [link] [pdf]

              • McGee et. al, Multi-task network for radar emitter detection and denoising NAECON 2023.. [pdf]

                • Information Retrieval

                Graph NN

                Graph Matching


              • Huihui Xu and Jundong Liu, Spatial-awareness spectral embedding (SASE) for robust shape matching, ICASSP 2013 [link] [ pdf]