Publications

  • Y. Patel, T. Shah, M.K. Dhar, T. Zhang, S. Gopalakrishnan, J. Niezgoda, and Z. Yu, “Integrated Image and Location Analysis for Wound Classification: A Deep Learning Approach”, Scientific Reports, 14:7043, 2024. [Nature Online]

  • M.K. Dhar, T. Zhang, Y. Patel, S. Gopalakrishnan, and Z. Yu, “FUSegNet: A Deep Convolutional Neural Network for Foot Ulcer Segmentation”, Biomedical Signal Processing & Control, 92:106057, 2024. [ScienceDirect]

  • K. Gopalakrishnan, M. Dhar, M. Deb, D. Sood, C. Parikh, A. Goudel, J. League, Z. Yu, M. Camilleri, N. Coelho-Prabhu, C. Leggett, S. Poigai Arunachalam, “A Novel 3D Convolutional Neural Network Based Deep Learning Model For Gastrointestinal Endoscopic Video Classification: Feasibility Study”, Pages S-1493, Gastroenterology, 2024. [AGA Online]

  • C. Wang, A. Mahbod, I. Ellinger, A. Galdran, S. Gopalakrishnan, J. Niezgoda, and Z. Yu, “FUSeg: The Foot Ulcer Segmentation Challenge”, Information, 15, 140, 2024. [MDPI]

  • H. Barzekar, Y. Patel, L. Tong, and Z. Yu, “MultiNet with Transformers: A Model for Cancer Diagnosis Using Images”, arXiv preprint:2301.09007, 2023. [arXiv]

  • F.H. Foomani, D.M. Anisuzzaman, J. Niezgoda, J. Niezgoda, W. Guns, S. Gopalakrishnan, and Z. Yu, “Synthesizing time-series wound prognosis factors from electronic medical records using generative adversarial networks”, Journal of Biomedical Informatics, 125:103972, 2022. [ScienceDirect]

  • H. Barzekar and Z. Yu, “C-Net: A Reliable Convolutional Neural Network for Biomedical Image Classification”, Expert Systems with Applications, 187:116003, 2022. [ScienceDirect]

  • D.M. Anisuzzaman, Y. Patel, J. Niezgoda, S. Gopalakrishnan, and Z. Yu, “A Mobile App for Wound Localization using Deep Learning”, IEEE Access, vol. 10, pp. 61398-61409, 2022. [IEEE Xplore]

  • D.M. Anisuzzaman, Y. Patel, B. Rostami, J. Niezgoda, S. Gopalakrishnan, and Z. Yu, “Multi-modal Wound Classification using Wound Image and Location by Deep Neural Network”, Scientific Reports, 12, 20057, 2022. [Nature Online]

  • M. Eisenmann, et al., “Biomedical Image Analysis Competitions: The State of Current Participation Practice”, arXiv preprint:2212.08568, 2022. [arXiv]

  • D.M. Anisuzzaman, Y. Patel, J. Niezgoda, S. Gopalakrishnan, and Z. Yu, “Wound Severity Classification using Deep Neural Network”, arXiv preprint:2204.07942, 2022. [arXiv]

  • D.M. Anisuzzaman, C. Wang, B. Rostami, S. Gopalakrishnan, J. Niezgoda, and Z. Yu, “Image Based Artificial Intelligence in Wound Assessment: A Systematic Review”, Advances in Wound Care, 11(12):687-709, 2022. [LiebertPub]

  • Y. Shi, J. Li, Z. Yu, Y. Li, Y Hu, and L. Wu, “Multi-Barley Seed Detection Using iPhone Images and YOLOv5 Model”, Foods, 11(21), 3531, 2022. [MDPI]

  • Y. Shi, Y. Patel, B. Rostami, H. Chen, L. Wu, Z. Yu, and Y. Li, “Barley Variety Identification by iPhone Images and Deep Learning”, Journal of the American Society of Brewing Chemists, 80(3):215-224, 2022. [Taylor & Francis Online]

  • D.M. Anisuzzaman, H. Barzekar, L. Tong, J. Luo, and Z. Yu, “A Deep Learning Study on Osteosarcoma Detection from Histological Images”, Biomedical Signal Processing and Control, 69:102931, 2021. [ScienceDirect]

  • B. Rostami, D.M. Anisuzzaman, C. Wang, S. Gopalakrishnan, J. Niezgoda, and Z. Yu, “Multiclass Wound Image Classification using an Ensemble Deep CNN-based Classifier”, Computers in Biology and Medicine, 134:104536, 2021. [ScienceDirect]

  • M.A. Sayed, X. Qin, R.J. Kate, D.M. Anisuzzaman, and Z. Yu, “Identification and analysis of misclassified work-zone crashes using text mining techniques”, Accident Analysis & Prevention, 159:106211, 2021. [ScienceDirect]

  • R.L. Boomen, Z. Yu, and Q. Liao, “Application of Deep Learning for Imaging-based Stream Gaging”, Water Resources Research, 57(11):e2021WR029980, 2021. [AGU-PUB]

  • C. Wang, D.M. Anisuzzaman, V. Williamson, M.K. Dhar, B. Rostami, J. Niezgoda, S. Gopalakrishnan, and Z. Yu, “Fully Automatic Wound Segmentation with Deep Convolutional Neural Networks”, Scientific Reports, 10:21897, 2020. [Nature Online].

  • H. Ghanbari-Ghalehjoughi, M. Eslami, S. Ahmadi-Kandjani, M. Ghanbari-Ghalehjoughi, and Z. Yu, “Multiple layer encryption and steganography via multi-channel ghost imaging”, Optics and Lasers in Engineering, 134:106227, 2020. [ScienceDirect]

  • F.S. Bashiri, R. Rostami, P. Peissig, R.M. D’Souza and Z. Yu, “An Application of Manifold Learning in Global Shape Descriptors”. Journal of Algorithms, 12(8): 171-192, 2019. [MDPI]

  • Y. Guo, K. Liu and Z. Yu, “Tetrahedron-Based Porous Scaffold Design for 3D Printing”. Journal of Designs, 3(1), 1-16, 2019. [MDPI]

  • F.S. Bashiri, A. Baghaie, R. Rostami, Z. Yu, and R.M. D’Souza, “Multi-Modal Medical Images Registration with Full or Partial Data: A Manifold Learning Approach”, Journal of Imaging, 5(5):1-24, 2019. [MDPI]

  • F.S. Bashiri, J.C. Badger, R.M. D’Souza, Z. Yu, and P. Peissig,, “Lung nodule classification using combined deep and spectral 3D shape features”. In Proceedings of IEEE International Conference on Biomedical and Health Informatics (BHI’19), pages 1-4, 2019. [IEEE Xplore]

  • C. Wang, Y. Guo, W. Chen, and Z. Yu, “Fully automatic intervertebral disc segmentation using multimodal 3D U-Net”, In Proceedings of IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC): Data Driven Intelligence for a Smarter World, pages 730-739, 2019. [IEEE Xplore]

  • R. Rostami, F.S. Bashiri, B. Rostami, and Z. Yu, “A Survey on Data-Driven 3D Shape Descriptors”. Computer Graphics Forum, 38(1): 356-393, 2018. [Willy]

  • H. Chen, Y. Guo, R. Rostami, S. Fan, K. Tang, and Z. Yu, “Porous Structure Design Using Parameterized Hexahedral Meshes and Triply Periodic Minimal Surfaces”. In Proceedings of Computer Graphics International (CGI), pages: 117-128, 2018. [ACM]

  • F.S. Bashiri, E. LaRose, J. Badger, R.M. D’Souza, Z. Yu, and P. Peissig, “Object Detection to Assist Visually Impaired People: A Deep Neural Network Adventure”. In Proceedings of 13th International Symposium on Visual Computing (ISVC), Lecture Notes in Computer Science, vol 11241, pp 500-510, 2018. [SpringerLink]

  • Y. Guo, K. Liu and Z. Yu, “Porous Structure Design in Tissue Engineering Using Anisotropic Radial Basis Functions”, In Proceedings of 13th International Symposium on Visual Computing (ISVC), Lecture Notes in Computer Science, vol 11241, pp 79-90, 2018. [SpringerLink]

  • A. Baghaie, C. Zhang, A. Bakhshinejad, H. A. Owen, H. Chao, R. M. D’Souza, and Z. Yu, “Slanted Support Window-Based Stereo Matching for Surface Reconstruction of Microscopic Samples”, Micron, 103:12-21, 2017. [ScienceDirect]

  • A. Baghaie, A. Tafti, H.A. Owen, R.M. D’Souza, and Z. Yu, “Three-Dimensional Reconstruction of Highly Complex Microscopic Samples Using Scanning Electron Microscopy and Optical Flow Estimation”, PLOS ONE, 12(4):e0175078, 2017. [PLOS ONE]

  • A. Baghaie, A. Tafti, H.A. Owen, R.M. D’Souza, and Z. Yu, “SD-SEM: Sparse-Dense Correspondence for 3D Reconstruction of Microscopic Samples”, Micron, 97:41-55, 2017. [ScienceDirect]

  • A. Baghaie, Z. Yu, and R. D’souza, “Involuntary Eye Motion Correction in Retinal Optical Coherence Tomography: Hardware or Software Solution?”, Medical Image Analysis, 37:129–145, 2017. [ScienceDirect]

  • A. Baghaie, R. D’souza, and Z. Yu, “Dense Descriptors for Optical Flow Estimation: A Comparative Study”, Journal of Imaging, 3(1), 12, 2017. [MDPI Online]

  • A.P. Tafti, A. Baghaie, M. Assefi, A. Nikolai, Z. Yu, H.R. Arabnia, and P. Peissig, “OCR as a Service: An Experimental Evaluation of Google Docs OCR, Tesseract, ABBYY FineReader, and Transym”, International Symposium on Visual Computing, Las Vegas, 2016.

  • E. Omrani, A.P. Tafti, M.F. Fathi, A.D. Moghadam, P. Rohatgi, R.M. D’Souza, and Z. Yu, “Tribological Study in Micro Scale Using 3D SEM Surface Reconstruction”, Tribology International, 103:309-315, 2016. [ScienceDirect]

  • A. Tafti, J.D. Holz, A. Baghaie, H.A. Owen, M. He, and Z. Yu, “3DSEM++: Adaptive and Intelligent 3D SEM Surface Reconstruction”, Micron, 87:33-45, 2016. [ScienceDirect]

  • M. Xu and Z. Yu, “3D Image Segmentation Based on Feature-Sensitive and Adaptive Tetrahedral Meshes”, IEEE International Conference on Image Processing, Phoenix (AZ), 2016. (accepted)

  • A. Baghaie, R. D’souza, and Z. Yu,  
    “Application of Independent Component Analysis Techniques in Speckle Noise Reduction of Retinal OCT Images”, Optik – International Journal for Light and Electron Optics, 127(15):5783-5791, 2016. [ScienceDirect]

  • Z. Gao, R. Rostami, X. Pang, Z. Fu, and Z. Yu, “Mesh Generation and Flexible Shape Comparisons for Bio-Molecules”, Molecular Based Mathematical Biology, 4:1-13, 2016. [De Gruyter]

  • A. Tafti, A. Baghaie, A.B. Kirkpatrick, J.D. Holz, H.A. Owen, R.M. D’Souza, and Z. Yu, “A Comparative Study on the Application of SIFT, SURF, BRIEF and ORB for 3D Surface Reconstruction of Electron Microscopy Images”, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2016. [Taylor & Francis Online]

  • E.O.Asante-Asamani, L. Wang, and Z. Yu, “A Cylindrical Basis Function for Solving Partial Differential Equations on Manifolds”, International Conference on Computational Science (ICCS), Vol 80, pages 233-244, 2016. [Procedia Computer Science]

  • Y. Jiang, Y. Xie, J. Ying, D. Xie, and Z. Yu, “SDPBS Web Server for Calculation of Electrostatics of Ionic Solvated Biomolecules”, Molecular Based Mathematical Biology, 3:179-196, 2015. [De Gruyter]

  • A. Tafti, A. Kirkpatrick, Z. Alavi, H. Owen, and Z. Yu, “Recent Advances in 3D SEM Surface Reconstruction”, Micron, 78:54-66, 2015. [ScienceDirect]

  • A. Tafti, A. Kirkpatrick, J. Holz, H. Owen, and Z. Yu, “3DSEM: A 3D Microscopy Dataset”, Data in Brief, 6:112-116, 2015. [ScienceDirect]

  • A. Tafti, H. Hassannia, D. Piziak and Z. Yu, “SeLibCV: A Service Library for Computer Vision Researchers”, International Symposium on Visual Computing, Las Vegas, LNCS 9475, pages 542-553, 2015. [SpringerLink]

  • A. Baghaie, Z. Yu, and R. D’souza, “State-of-the-art in Retinal Optical Coherence Tomography Image Analysis”, Quantitative Imaging in Medicine and Surgery, 5(4):603-617, 2015. [AME Publishing]

  • A. Baghaie, R. D’souza, and Z. Yu, “Sparse and Low Rank Decomposition Based Batch Image Alignment for Speckle Reduction of Retinal OCT Images”, International Symposium on Biomedical Imaging, New York, pages 226-230, 2015. [IEEE-Xplore]

  • A. Baghaie, R. D’souza, and Z. Yu, “Dense Correspondence and Optical Flow Estimation Using Gabor, Schmid and Steerable Descriptors”, International Symposium on Visual Computing, Las Vegas, LNCS 9474, pages 406-415, 2015. [SpringerLink]

  • A. Baghaie and Z. Yu, “Structure Tensor Based Image Interpolation Method”, International Journal of Electronics and Communications, 69(2): 515-522, 2015. [ScienceDirect]

  • A.P. Tafti, A.B. Kirkpatrick, H.A. Owen, and Z. Yu, “3D Microscopy Vision Using Multiple View Geometry and Differential Evolutionary Approaches”, The 10th International Symposium on Visual Computing (ISVC), Las Vegas, LNCS 8888, pages 141-152, 2014. [SpringerLink]

  • A. Baghaie, Z. Yu, and R. D’souza, “Fast Mesh-Based Medical Image Registration”, The 10th International Symposium on Visual Computing (ISVC), Las Vegas, LNCS 8888, pages 1-10, 2014. [SpringerLink]

  • K. Liu, M. Xu, and Z. Yu, “Feature-preserving Image Restoration from Adaptive Triangular Meshes”, ACCV Workshop on Emerging Topics on Image Restoration and Enhancement, LNCS 9009, Pages 31-46, Singapore, 2014. [SpringerLink]

  • Z. Li, S. Qin, Z. Yu, Y. Jin, “Skeleton-based Shape Analysis of Protein Models”, Journal of Molecular Graphics and Modeling, 53:72-81, 2014. [ScienceDirect]

  • Z. Li, S. Qin, X. Jin, Z. Yu, and J. Lin, “Skeleton-Enhanced Line Drawings for 3D Models”, Graphical Models, 76(6):620-632, 2014. [ScienceDirect]

  • P. Sarkar, E. Bosneaga, E. Yap, J. Das, W.-T. Tsai, A. Cabal, E. Neuhaus, D. Maji, S. Kumar, M. Joo, S. Yakovlev, R. Csencsits, Z. Yu, C. Bajaj, K. H. Downing, M. Auer, “Electron Tomography of Cryo-immobilized Plant Tissue: A Novel Approach to Studying 3D Macromolecular Architecture of Mature Plant Cell Walls in Situ”,
    PLOS ONE 9(9): e106928, 2014. [PLOS ONE]

  • Z. Gao, Z. Yu, and X. Pang, “A Compact Shape Descriptor for Triangular Surface Meshes”, Computer-Aided Design, 53: 62-69, 2014. [ScienceDirect]

  • J. Wang, Z. Yu, M. Wei, C. Tan, N. Dai, and X. Zhang, “Robust Reconstruction of 2D Curves from Scattered Noisy Point Data”, Computer-Aided Design, 50:27-40, 2014. [ScienceDirect]

  • Z. Yu, J. Wang, Z. Gao, M. Xu, and M. Hoshijima, “New Software Developments for Quality Mesh Generation and Optimization from Biomedical Imaging Data”, Computer Methods and Programs in Biomedicine, 113(1):226-240, 2014. [ScienceDirect]

  • K. Liu, G. Yao, and Z. Yu, “Parallel Acceleration for Modeling of Calcium Dynamics in Cardiac Myocytes”, Bio-Medical Materials and Engineering, 24:1417-1424, 2014. [IOS Press]

  • U.Z. George, J. Wang, and Z. Yu, “Numerical Analysis of the Effect of T-tubule Location on Calcium Transient in Ventricular Myocytes”, Bio-Medical Materials and Engineering, 24:1299-1306, 2014. [IOS Press]

  • M. Xu, Z. Gao, and Z. Yu, “Feature-Sensitive and Adaptive Mesh Generation of Grayscale Images”, The 4th Conference on Computational Modeling of Objects Presented in Images: Fundamentals, Methods and Applications , Pittsburgh, LNCS 8641, pages 204-215, 2014. [SpringerLink]

  • A. Baghaie and Z. Yu, “Curvature-Based Registration For Slice Interpolation Of Medical Images”, The 4th Conference on Computational Modeling of Objects Presented in Images: Fundamentals, Methods and Applications , Pittsburgh, LNCS 8641, pages 69-80, 2014. [SpringerLink]

  • Q. Sang, J. Zhang, and Z. Yu, “Robust Non-Rigid Point Registration Based on Feature-dependant Finite Mixture Model”, Pattern Recognition Letters, 34(13): 1557-1565, 2013. [ScienceDirect]

  • J. Wang, K. Xu, L. Liu, J. Cao, S. Liu, Z. Yu and X. Gu, “Consolidation of Low-quality Point Clouds from Outdoor Scenes”, Special Issue on SGP’13, Computer Graphics Forum, 32(5): 207-216, 2013. [Wiley Online]

  • J. Wong, D. Baddeley, E.A. Bushong, Z. Yu, M.H. Ellisman, M. Hoshijima, and C. Soeller, “Nanoscale Distribution of Ryanodine Receptors and Caveolin-3 in Mouse Ventricular Myocytes: Dilation of T-tubules Near Junctions”, Biophysical Journal, 104(11):L22-L24, 2013. [ScienceDirect]

  • J. Wang, Z. Yu, W. Zhu and J. Cao, “Feature-Preserving Surface Reconstruction from Unoriented, Noisy Point Data”, Computer Graphics Forum, 32(1): 164-176, 2013. [Wiley Online]

  • Z. Gao, Z. Yu, and M. Holst, “Feature-Preserving Surface Mesh Smoothing via Suboptimal Delaunay Triangulation”, Graphical Models, 75(1): 23-38, 2013. [ScienceDirect]

  • J. Wang, D. Gu, Z. Gao, Z. Yu, C. Tan, and L. Zhou, “Feature-based Solid Model Reconstruction”, Journal of Computing and Information Science in Engineering, 13(1): 011004(1-13), 2013. [ASME]

  • Z. Gao, Z. Yu, and M. Holst, “Quality Tetrahedral Mesh Smoothing via Boundary-Optimized Delaunay Triangulation”, Computer Aided Geometric Design, 29(9):707-721, 2012. [ScienceDirect]

  • J. Wang, D. Gu, Z. Yu, C. Tan, and L. Zhou, “A Framework for 3D Model Reconstruction in Reverse Engineering”, Computer & Industrial Engineering, 63(4):1189-1200, 2012. [ScienceDirect]

  • J. Hake, A.G. Edwards, Z. Yu, P.M. Kekenes-Huskey, A.P. Michailova, J.A. McCammon, M.J. Holst, M. Hoshijima, and A.D. McCulloch, “Modeling Cardiac Calcium Sparks in a Three-Dimensional Reconstruction of a Calcium Release Unit”, The Journal of Physiology, 590(18):4403-4422, 2012. [Wiley Online]

  • J. Wang, X. Zhang, and Z. Yu, “A Cascaded Approach for Feature-Preserving Surface Mesh Denoising”, Computer-Aided Design, 44(7):597-610, 2012. [ScienceDirect]

  • J. Wang and Z. Yu, “Feature-Sensitive Tetrahedral Mesh Generation with Guaranteed Quality”, Computer-Aided Design, 44(5):400-412, 2012. [ScienceDirect]

  • J. Wang and Z. Yu, “Feature-Preserving Mesh Denoising via Anisotropic Surface Fitting”, Journal of Computer Science and Technology, 27(1):163-173, 2012. [SpringerLink]

  • M. Holst, J.A. McCammon, Z. Yu, Y. Zhou, and Y. Zhu, “Adaptive Finite Element Modeling Techniques for the Poisson-Boltzmann Equation”, Communications in Computational Physics (CiCP), 11(1):179-214, 2012. [PubMed]

  • G. Yao and Z. Yu, “A Localized Meshless Approach for Modeling Spatial-temporal Calcium Dynamics in Ventricular Myocytes”,International Journal for Numerical Methods in Biomedical Engineering, 28(2):187-204, 2012. [Wiley Online]

  • L. Wang, Z. Yu, and C. Pan, “A Unified Level Set Framework Utilizing Parameter Priors for Medical Image Segmentation”, SCIENCE CHINA: Information Sciences, 55(10):1-14, 2012. [SpringerLink]

  • Z. Gao, Z. Yu, and J. Wang, “An Optimization-Based Iterative Approach to Tetrahedral Mesh Smoothing”, invited book chapter in Image-based Geometric Modeling and Mesh Generation (Edited by Y. Zhang), pages 143-157, Springer, 2012. [SpringerLink]

  • M. Xu, J. Wang, and Z. Yu, “Image Edge Enhancement and Segmentation via Randomized Shortest Paths”, The 5th International Conference on BioMedical Engineering and Informatics , pages 290-294, China, 2012. [IEEE-Xplore]

  • Q. Sang, J. Zhang, and Z. Yu, “Non-Rigid Point Set Registration: A Bi-directional Approach”, The 37th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pages 693-696, Japan, 2012. [IEEE-Xplore]

  • J. Wang and Z. Yu,  
    “Quadratic Curve and Surface Fitting via Squared Distance Minimization”, Computers & Graphics, 35(6):1035-1050, 2011. [ScienceDirect]

  • Z. Yu, G. Yao, M. Hoshijima, A. Michailova, and M. Holst,  
    “Multi-Scale Modeling of Calcium Dynamics in Ventricular Myocytes with
    Realistic Transverse Tubules”,
    IEEE Transactions on Biomedical Engineering, 58(10):2947-2951, 2011. [IEEE-Xplore]

  • J. Wang and Z. Yu,  
    “Surface Feature based Mesh Segmentation”,
    Special Issue on Shape Modeling (SMI’11), Computers & Graphics, 35(3):661-667, 2011. [ScienceDirect]

  • J. Wang and Z. Yu,  
    “Geometric Decomposition of 3D Surface Meshes using Morse Theory and Region Growing”,
    International Journal of Advanced Manufacturing Technology, 56(9-12):1091-1103, 2011.
    [SpringerLink]

  • J. Wang and Z. Yu,  
    “Quality Mesh Smoothing via Local Surface Fitting and Optimum Projection”,
    Graphical Models, 73:127-139, 2011.
    [ScienceDirect]

  • Z. Yu, M. Xu, and Z. Gao,  
    “Biomedical Image Segmentation via Constrained Graph Cuts and Pre-segmentation”, Proc. of the 33rd Int’l Conf. of IEEE Engineering in Medicine and Biology Society, pages 5714-5717, Boston, 2011.
    [IEEE-Xplore]

  • Y. Cheng, Z. Yu, M. Hoshijima, M.J. Holst, A.D. McCulloch, J.A. McCammon, and A.P. Michailova,  
    “Numerical Analysis of Calcium Signaling in Rat Ventricular Myocytes with Realistic Transverse-axial Tubular Geometry and Inhibited Sarcoplasmic Reticulum”,
    PLoS Computational Biology, 6(10): e1000972(1-16), 2010. [PLoS] [PubMed]

  • L. Wang, Z. Yu, and C. Pan,  
    “Medical Image Segmentation Based on Novel Local Order Energy”,
    Proceedings of the 10th Asian Conference on Computer Vision, pages 148-159, Queenstown, New Zealand, 2010.
    [SpringerLink]

  • J. Wang and Z. Yu,  
    “A Morse-Theory based Method for Segmentation of Triangulated Freeform Surfaces”,
    Proceedings of the 5th International Symposium on Visual Computing, LNCS 5876: pages 939?48, Las Vegas, 2009.
    [SpringerLink]

  • J. Wang and Z. Yu,  
    “A Novel Method for Surface Mesh Smoothing: Applications in Biomedical Modeling”,
    Proceedings of the 18th International Meshing Roundtable, pages 195?10, Salt Lake City, 2009.
    [SpringerLink]

  • J. Fan and Z. Yu,  
    “A Univariate Model of Calcium Release in the Dyadic Cleft of Cardiac Myocytes”,
    Proceedings of the 31st Int’l Conf. of IEEE Engineering in Medicine and Biology Society, pages 4499-4503, Minneapolis, 2009.
    [IEEE-Xplore]
    [PubMed]

  • Z. Yu,  
    “A List-based Method for Fast Generation of Molecular Surfaces”,
    Proceedings of the 31st Int’l Conf. of IEEE Engineering in Medicine and Biology Society, pages 5909-5912, Minneapolis, 2009.
    [IEEE-Xplore]
    [PubMed]

  • A.A. Gorfe, B. Lu, Z. Yu, and J.A. McCammon,  
    “Enzymatic Activity versus Structural Dynamics: The Case of Acetylcholinesterase Tetramer”,  
    Biophysical Journal, 97(3):897-905, 2009.
    [Biophys. J.]
    [PubMed]

  • T. Hayashi, M.E. Martone, Z. Yu, A. Thor, M. Doi, M. Holst, M.H. Ellisman, and M. Hoshijima,  
    “Three-dimensional Reconstruction Reveals New Details of Membrane Systems for Calcium Signaling in the Heart”,  
    Journal of Cell Science, 122(7):1005-1013, 2009.
    [JCS Online]
    [PubMed]

  • S. Lu, A. Michailova, J. Saucerman, Y. Cheng, Z. Yu, T. Kaiser, W. Li, R.E. Banks, M. Holst, J.A. McCammon, T. Hayashi, M. Hoshijima, P. Arzberger, and A.D. McCulloch,  
    “Multiscale Modeling in Rodent Ventricular Myocytes”,  
    IEEE Engineering in Medicine and Biology Magazine, 28(2):46-57, 2009.
    [IEEE-Xplore]
    [PubMed]

  • X. Yan, Z. Yu, P. Zhang, A.J. Batistti, P.R. Chipman, C.L. Bajaj, M. Bergoin, M.G. Rossmann, and T.S. Baker,  
    “The Capsid Proteins of a Large, Icosahedral dsDNA Virus”,  
    Journal of Molecular Biology, 385(4):1287-1299, 2009.
    [ScienceDirect]
    [PubMed]

  • Z. Yu, M. Holst, T. Hayashi, C.L. Bajaj, M.H. Ellisman, J.A. McCammon, and M. Hoshijima,  
    “Three-Dimensional Geometric Modeling of Membrane-bound Organelles in Ventricular Myocytes: Bridging the Gap between Microscopic Imaging and Mathematical Simulation”,  
    Journal of Structural Biology, 164(3):304-313, 2008.
    [ScienceDirect]
    [PubMed]

  • Y. Cheng, C. Chang, Z. Yu, Y. Zhang, M. Sun, T.S. Leyh, M. Holst, and J.A. McCammon,  
    “Diffusional Channeling in the Sulfate Activating Complex: combined continuum modeling and coarse-grained Brownian dynamics studies”,  
    Biophysical Journal, 95(10):4659-4667, 2008.
    [Biophys. J.]
    [PubMed]

  • Z. Yu, M. Holst, and J.A. McCammon,  
    “High-Fidelity Geometric Modelling for Biomedical Applications”,  
    Finite Elements in Analysis and Design, 44(11):715-723, 2008.
    [ScienceDirect]
    [ACM-Portal]

  • Z. Yu, M. Holst, Y. Cheng, and J.A. McCammon,  
    “Feature-Preserving Adaptive Mesh Generation for Molecular Shape Modeling and Simulation”,  
    Journal of Molecular Graphics and Modeling, 26(8):1370-1380, 2008.
    [ScienceDirect]
    [PubMed]

  • Z. Yu and C.L. Bajaj,  
    “Computational Approaches for Automatic Structural Analysis of Large Bio-molecular Complexes”,  
    IEEE/ACM Transactions on Computational Biology and Bioinformatics, 5(4):568-582, 2008.
    [PDF]
    [IEEE-ComputerSociety] [PubMed]

  • M. Baker, Z. Yu, W. Chiu, and C.L. Bajaj,  
    “Automated Segmentation of Molecular Subunits in Electron Cryomicroscopy Density Maps”,  
    Journal of Structural Biology, 156(3):432-441, 2006.
    [ScienceDirect]
    [PubMed]

  • C.L. Bajaj, S. Goswami, Z. Yu, Y. Zhang, Y. Bazilevs, and T. Hughes,  
    “Patient Specific Heart Models from High Resolution CT”,  
    Proceedings of International Symposium on Computational Modeling of Objects Represented in Images (CompIMAGE), pages 157-165, Portugal, 2006.
    [PDF]

  • Z. Yu and C.L. Bajaj,  
    “A Structure Tensor Approach for 3D Image Skeletonization: Applications in Protein Secondary Structural Analysis”, 
    Proceedings of IEEE International Conference on Image Processing (ICIP’06), pages 2513-2516, Atlanta, GA, 2006.
    [PDF]
    [IEEE-Xplore]

  • Z. Yu and C.L. Bajaj,  
    “Computational Approaches for Automatic Structural Analysis of Large Bio-molecular Complexes”,
    Technical Report TR-06-05, Department of Computer Sciences, The University of Texas at Austin, January 09, 2006.

  • Z. Yu and C.L. Bajaj,  
    “Automatic Ultra-structure Segmentation of Reconstructed Cryo-EM Maps of Icosahedral Viruses”, 
    IEEE Transactions on Image Processing, 14(9):1324-1337, September 2005.
    [PDF]
    [IEEE-Xplore]
    [PubMed]

  • C.L. Bajaj and Z. Yu, 
    “Geometric Processing of Reconstructed 3D Maps of Molecular Complexes”, 
    invited book chapter in Handbook of Computational Molecular Biology, Edited by S. Aluru, Chapman & Hall/CRC Press, Computer and Information Science Series, December 2005.
    [CRC-Press]
    [Amazon]

  • Z. Yu and C.L. Bajaj,  
    “Detecting Circular and Rectangular Particles Based on Geometric Feature Detection in Electron Micrographs”, 
    Journal of Structural Biology, 145(1-2):168-180, January 2004.
    [ScienceDirect]
    [PubMed]

  • Z. Yu and C.L. Bajaj,  
    “A Fast and Adaptive Algorithm for Image Contrast Enhancement”, 
    Proceedings of 2004 IEEE International Conference on Image Processing (ICIP’04), pages 1001-1004, Singapore, October 2004.
    [PDF]
    [IEEE-Xplore]

  • Z. Yu and C.L. Bajaj,  
    “A Segmentation-Free Approach for Skeletonization of Gray-Scale Images via Anisotropic Vector Diffusion”, 
    Proceedings of 2004 IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’04), volume 1, pages 415-420, Washington DC, June 2004.
    [PDF]
    [IEEE-ComputerSociety]

  • Z. Yu and C.L. Bajaj,  
    “Visualization of Icosahedral Virus Structures from Reconstructed Volumetric Maps”,
    Technical Report TR-04-10, Department of Computer Sciences, The University of Texas at Austin, April 9, 2004.

  • C.L. Bajaj, Z. Yu, and M. Auer,  
    “Volumetric Feature Extraction and Visualization of Tomographic Molecular Imaging”,  
    Journal of Structural Biology, 144(1-2):132-143, October 2003.
    [ScienceDirect]
    [PubMed]

  • Z. Yu and C.L. Bajaj,  
    “A Gravitation-Based Clustering Method and Its Applications in 3D Electron Microscopy Imaging”, 
    Proceedings of the 5th International Conference on Advances in Pattern Recognition (ICAPR’03), pages 137-140, Calcutta, India, December 2003.
    [PDF]

  • C.L. Bajaj, Z. Yu, and M. Auer,  
    “Volumetric Filtering, Feature Extraction, and Visualization of Volumetric Tomographic Molecular Imaging”,
    Technical Report TR-03-31, Department of Computer Sciences, The University of Texas at Austin, July 28, 2003.

  • Z. Yu and C.L. Bajaj,  
    “A Geometric Feature Detection Approach to Particle Picking in Electron Micrographs”,
    Technical Report TR-03-30, Department of Computer Sciences, The University of Texas at Austin, July 28, 2003.

  • Z. Yu and C.L. Bajaj,  
    “Anisotropic Vector Diffusion in Image Smoothing”, 
    Proceedings of the 9th IEEE International Conference on Image Processing (ICIP’02), volume 1, pages 828-831, Rochester, New York, September 2002.
    [PDF]
    [IEEE-Xplore]

  • Z. Yu and C.L. Bajaj, 
    “Image Segmentation Using Gradient Vector Diffusion and Region Merging”, 
    Proceedings of the 16th International Conference on Pattern Recognition (ICPR’02), volume 2, pages 941-944, Quebec, Canada, August 2002.
    [PDF]
    [IEEE-Xplore]
    [IEEE-ComputerSociety]

  • Z. Yu and C.L. Bajaj, 
    “Normalized Gradient Vector Diffusion and Image Segmentation”, 
    Proceedings of the 7th European Conference on Computer Vision (ECCV’02), Lecture Notes in Computer Science, volume 2352, pages 517-530, Copenhagen, Denmark, May 2002.
    [PDF]
    [SpringerLink]
    [ACM-Portal]

  • J.F. Delerue, E. Perrier, Z. Yu, and B. Velde,  
    “New Algorithms in 3D Image Analysis and Their Application to the Measurement of a Spatialized Pore Size Distribution in Soils”,  
    Journal of Physics and Chemistry of the Earth, 24(7):639-644, October 1999.
    [ScienceDirect]

  • Z. Yu, J.F. Delerue, and S. Ma, 
    “3D Euclidean distance transformation”, 
    Proceedings of the International Symposium on Image, Speech, Signal Processing and Robotics (ISSPR’98), pages 67-72, Hong Kong, September 1998.
    [PDF]