Personal profile
Research interests
Dr. Gastounioti is developing a research program on translational breast imaging research towards prediction, early diagnosis, prognosis, and response to treatment for breast cancer. Her research combines elements of computational breast image analysis, artificial intelligence, and informatics, to build technologies with a potential for clinical impact in advancing breast cancer screening and prevention strategies.
Mentoring
Dr. Gastounioti is actively looking for motivated students, postdoctoral researchers, and medical trainees interested in computational breast imaging research and artificial intelligence. We are dedicated to maintaining a vibrant and diverse working environment and to providing as many opportunities as possible for young trainees to pursue their scientific and professional goals.
Available to Mentor:
- Undergraduate Students
- PhD Students
- Postdocs
- Residents and Fellows
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Collaborations and top research areas from the last five years
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Head-to-head comparisons of breast density assessment models using deep learning on digital and synthetic mammograms
Anant, K., López, J. H., Cui, J., Gupta, S. D., Bennett, D. L. & Gastounioti, A., Mar 1 2026, In: Journal of Medical Imaging. 13, 2, 024503.Research output: Contribution to journal › Article › peer-review
Open Access -
Associations of early-adulthood adiposity with breast parenchymal tissue complexity within premenopausal women
Das Gupta, S., Getz, K., Hernandez Lopez, J., Bennett, D. L., Toriola, A. T. & Gastounioti, A., Dec 2025, In: Breast Cancer Research. 27, 1, 188.Research output: Contribution to journal › Article › peer-review
Open Access -
Radiomic Parenchymal Phenotypes of Breast Texture from Mammography and Association with Risk of Breast Cancer
Winham, S. J., McCarthy, A. M., Scott, C. G., Gastounioti, A., Horng, H., Norman, A. D., Mankowski, W. C., Pantalone, L., Jensen, M. R., Acciavatti, R. J., Maidment, A. D. A., Cohen, E. A., Brandt, K. R., Conant, E. F., Kerlikowske, K. M., Kontos, D. & Vachon, C. M., May 2025, In: Radiology. 315, 2, e240281.Research output: Contribution to journal › Article › peer-review
Open Access8 Link opens in a new tab Scopus citations -
Subgroup evaluation to understand performance gaps in deep learning-based classification of regions of interest on mammography
Woo, M. J., Zhang, L., Brown-Mulry, B., Hwang, I. C., Gichoya, J. W., Gastounioti, A., Banerjee, I., Seyyed-Kalantari, L. & Trivedi, H., Apr 2025, In: PLOS Digital Health. 4, 4, e0000811.Research output: Contribution to journal › Article › peer-review
Open Access3 Link opens in a new tab Scopus citations -
Advancing Volumetric Breast Density Segmentation: A Deep Learning Approach with Digital Breast Tomosynthesis
Doiphode, N., Ahluwalia, V. S., Mankowski, W. C., Cohen, E. A., Pati, S., Pantalone, L., Bakas, S., Brooks, A., Vachon, C. M., Conant, E. F., Gastounioti, A. & Kontos, D., 2024, 17th International Workshop on Breast Imaging, IWBI 2024. Giger, M. L., Whitney, H. M., Drukker, K. & Li, H. (eds.). SPIE, 131740O. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 13174).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review