Publications

C. E. Harris, Liu, L., Kennady, D. Adhithya, Bakic, P. R., and Makrogiannis, S., “Breast density classification and decision explainability by deep sparse approximations”, in Medical Imaging 2026: Computer-Aided Diagnosis, 2026.

L. Carlos Alm Da Silva, Kaymaz, B., Makrogiannis, S., Rogers, K. J., Kecskemethy, H. H., Nikam, R., Bowen, J. Richard, Gould, S. W., and Thacker, M. M., “Measurements of acetabular morphology in healthy children using multiplanar computed tomography reconstructions”, Journal of Pediatric Orthopaedics B, vol. 35, pp. 164–172, 2026.

Y. Wang, Makrogiannis, S., and Kambhamettu, C., “NeXt2Former-CD: Efficient Remote Sensing Change Detection with Modern Vision Architectures”. 2026.

M. N. Ibrahim, Liu, L., Annasamudram, N. V., Fishbein, K., Spencer, R. G., and Makrogiannis, S., “Segmentation of thigh muscle groups in volumetric fat- and water-suppressed MRI by a hierarchical transformer model”, in Medical Imaging 2026: Image Processing, 2026.

C. E. Harris, Liu, L., Almeida, L., Kassick, C., and Makrogiannis, S., “Artificial intelligence in pediatric osteopenia diagnosis: evaluating deep network classification and model interpretability using wrist X-rays”, Bone Reports, vol. 25, p. 101845, 2025.

S. Makrogiannis, “Foundation models for healthcare: innovations in generative AI, computer vision, language models, and multimodal systems”, Frontiers in Computer Science, vol. 7, p. 1744581, 2025.

L. Carlos Alm Da Silva, Kaymaz, B., Makrogiannis, S., Rogers, K. J., Kecskemethy, H. H., Nikam, R., Bowen, J. Richard, Gould, S. W., and Thacker, M. M., “Measurements of acetabular morphology in healthy children using multiplanar computed tomography reconstructions”, Journal of Pediatric Orthopaedics B, pp. 10–1097, 2025.

C. E. Harris, Liu, L., and Makrogiannis, S., “Pediatric osteopenia prediction and interpretation in wrist x-rays”, in Medical Imaging 2025: Computer-Aided Diagnosis, 2025.

N. Annasamudram, Zhao, J., Oluwadare, O., Prashanth, A., and Makrogiannis, S., “Scale selection and machine learning based cell segmentation and tracking in time lapse microscopy”, Scientific Reports, vol. 15, p. 11717, 2025.

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.

C. E. Harris, Okorie, U., Bakic, P. R., and Makrogiannis, S., “Evaluating breast density classification by sparse approximation classifiers and deep networks using simulated digital mammograms”, in Virtual Imaging Trials in Medicine, 2024.

N. Annasamudram and Makrogiannis, S., “A Joint Scale Analysis And Machine Learning Framework For Cell Detection And Segmentation In Time Lapse Microscopy”, in 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024.

C. Harris, Okorie, U., and Makrogiannis, S., “Mammographic Breast Density Classification by Integration of Deep Dictionaries and Multi-Model Sparse Approximations”, in 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 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.

X. Yue, Stauff, E., Boyapati, S., Langhans, S. A., Xu, W., Makrogiannis, S., Okorie, U. J., Okorie, A. M., Kandula, V. V. R., Kecskemethy, H. H., Nikam, R. M., Averill, L. W., and Shaffer, T. H., “PET Imaging of Neurofibromatosis Type 1 with a Fluorine-18 Labeled Tryptophan Radiotracer”, Pharmaceuticals, vol. 17, p. 685, 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.

S. Makrogiannis, “Editorial for "Diagnosis of Sarcopenia Using the L3 Skeletal Muscle Index Estimated from the L1 Skeletal Muscle Index on MR Images in Patients with Cirrhosis"”, Journal of Magnetic Resonance Imaging, 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 and Zheng, K., “AIM in Osteoporosis”, in Artificial Intelligence in Medicine, N. Lidströmer and Ashrafian, H., Eds. Cham: Springer International Publishing, 2022, pp. 785–801.

S. Makrogiannis, “Editorial for “Cross-Cohort Automatic Knee MRI Segmentation with Multi-Planar U-Nets””, Journal of Magnetic Resonance Imaging, vol. 55, pp. 1664-1665, 2022.

Q. Yang, Yu, X., Lee, H. Hin, Tang, Y., Bao, S., Gravenstein, K. S., Moore, A. Zenobia, Makrogiannis, S., Ferrucci, L., and Landman, B. A., “Label efficient segmentation of single slice thigh CT with two-stage pseudo labels”, Journal of Medical Imaging, vol. 9, p. 052405, 2022.

S. Makrogiannis, Okorie, A., Di Iorio, A., Bandinelli, S., and Ferrucci, L., “Multi-atlas segmentation and quantification of muscle, bone and subcutaneous adipose tissue in the lower leg using peripheral quantitative computed tomography”, Frontiers in physiology, vol. 13, p. 951368, 2022.