Publications

N. V. Annasamudram, Okorie, A. M., Spencer, R. G., Kalyani, R. R., Yang, Q., Landman, B. A., Ferrucci, L., and Makrogiannis, S., “Deep network and multi-atlas segmentation fusion for delineation of thigh muscle groups in three-dimensional water–fat separated MRI”, Journal of Medical Imaging, vol. 11, p. 054003, 2024.

N. V. Annasamudram, Okorie, A. M., Spencer, R. G., Kalyani, R. R., Yang, Q., Landman, B. A., Ferrucci, L., and Makrogiannis, S., “Multi-method and multi-atlas segmentation fusion for delineation of thigh muscle groups in 3D water-fat separated MRI”, in Medical Imaging 2024: Image Processing, 2024.

C. E. Harris and Makrogiannis, S., “Breast mass characterization using sparse approximations of patch-sampled deep features”, in Medical Imaging 2023: Computer-Aided Diagnosis, 2023.

Y. Wang, Williams, O., Annasamudram, N., and Makrogiannis, S., “Live Cell Segmentation and Tracking Techniques”, in Intelligent Video Analytics: Clustering and Classification Applications, E. Alfy Georg Zhou, Ed. CRC Press, 2023.

A. Okorie, Makrogiannis, S., Spencer, R., Kalyani, R., and Ferrucci, L., “Semantic segmentation of individual muscle groups in 3D thigh MRI”, in Medical Imaging 2023: Image Processing, 2023.

Q. Yang, Yu, X., Lee, H. Hin, Cai, L. Y., Xu, K., Bao, S., Huo, Y., Moore, A. Zenobia, Makrogiannis, S., Ferrucci, L., and Landman, B. A., “Single slice thigh CT muscle group segmentation with domain adaptation and self-training”, Journal of Medical Imaging, vol. 10, p. 044001, 2023.

C. Harris, Okorie, U., and Makrogiannis, S., “Spatially localized sparse approximations of deep features for breast mass characterization”, Mathematical Biosciences and Engineering, vol. 20, pp. 15859-15882, 2023.

S. Makrogiannis, Zheng, K., and Harris, C., “Discriminative Localized Sparse Approximations for Mass Characterization in Mammograms”, Frontiers in Oncology, 2021.

S. Makrogiannis, Zheng, K., and Harris, C., “Sparse analysis of deep features for characterization of breast masses”, in Medical Imaging 2021: Computer-Aided Diagnosis, 2021.

S. Makrogiannis, Annasamudram, N., Wang, Y., Miranda, H., and Zheng, K., “A System for Spatio-Temporal Cell Detection and Segmentation in Time-Lapse Microscopy”, in Workshop on Machine Learning and Artificial Intelligence in Bioinformatics and Medical Informatics (MABM 2021) in conjunction with 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021.

S. Makrogiannis, Harris, C. E., and Zheng, K., “Discriminative Localized Sparse Representations for Breast Cancer Screening”, in Mathematical and Computational Oncology - Second International Symposium, ISMCO 2020, San Diego, CA, USA, October 8-10, 2020, Proceedings, 2020.

K. Zheng, Harris, C. E., Jennane, R., and Makrogiannis, S., “Integrative blockwise sparse analysis for tissue characterization and classification”, Artificial Intelligence in Medicine, vol. 107, p. 101885, 2020.

K. Zheng, Harris, C., Bakic, P., and Makrogiannis, S., “Spatially localized sparse representations for breast lesion characterization”, Computers in Biology and Medicine, vol. 123, p. 103914, 2020.

K. Zheng, Jennane, R., and Makrogiannis, S., “Ensembles of Sparse Classifiers for Osteoporosis Characterization in Digital Radiographs”, in SPIE Medical Imaging 2019: Computer-Aided Diagnosis, 2019.

A. Okorie and Makrogiannis, S., “Region-based image registration for remote sensing imagery”, Computer Vision and Image Understanding, vol. 189, p. 102825, 2019.

S. Makrogiannis, Boukari, F., and Ferrucci, L., “Automated skeletal tissue quantification in the lower leg using peripheral quantitative computed tomography”, Physiological Measurement, vol. 39, p. 035011, 2018.

N. V. Orlov, Makrogiannis, S., Ferrucci, L., and Goldberg, I. G., “Differential Aging Signals in Abdominal CT Scans”, Academic Radiology, vol. 24, no. 12, pp. 1535 - 1543, 2017.

N. Melikechi, Markushin, Y., Connolly, D. C., Lasue, J., Ewusi-Annan, E., and Makrogiannis, S., “Age-specific discrimination of blood plasma samples of healthy and ovarian cancer prone mice using laser-induced breakdown spectroscopy”, Spectrochimica Acta Part B: Atomic Spectroscopy, vol. 123, pp. 33 - 41, 2016.

F. Boukari and Makrogiannis, S., “Joint Level-Set and Spatio-Temporal Motion Detection for Cell Segmentation”, BMC Medical Genomics, vol. 9 Suppl 2, 2016.

K. Zheng and Makrogiannis, S., “A Pattern Recognition System for Bone Texture Characterization from Digital Radiography,”, IEEE International Conference on Engineering in Medicine and Biology. pp. 1034-1037, 2016.

S. Makrogiannis and Bourbakis, N. G., “Editorial”, International Journal on Artificial Intelligence Tools, vol. 21, 2012.

N. G. Bourbakis, Makrogiannis, S., and Kapogiannis, D., “A Synergistic Model for Monitoring Brain's Changes: A Case Study”, in ICTAI, 2011, pp. 1093-1098.

S. Makrogiannis, Serai, S., Fishbein, K. W., Laney, W., Schreiber, C., Ershler, W. B., Ferrucci, L., and Spencer, R. G. S., “Automated Quantification of Muscle and Fat in the Thigh from Water-, Fat- and Non-suppressed MR Images”, in BIBE, 2010, pp. 52-57.

S. Makrogiannis and Bourbakis, N. G., “Efficient registration of multitemporal and multisensor aerial images based on alignment of nonparametric edge features”, J. Electronic Imaging, vol. 19, p. 013002, 2010.

S. Makrogiannis, Bhotika, R., Miller, J. V., Skinner, J., and Vass, M., “Nonparametric Intensity Priors for Level Set Segmentation of Low Contrast Structures”, in MICCAI (1), 2009, pp. 239-246.