Welcome to my personal website!
My research involves the implementation of deep learning techniques to accelerate the acquisition of dynamic images from magnetic resonance imaging (MRI) with a high spatio-temporal resolution for quantitative imaging.
Additionally, I analyze dynamic contrast-enhanced (DCE) MRI data from breast imaging using perfusion models to extract quantitative tissue information that may inform screening and mathematical modeling efforts.
I am formally advised by Thomas Yankeelov, Ph.D. in the Center for Computational Oncology and informally advised by Jonathan Tamir, Ph.D. in the Department of Electrical and Computer Engineering at UT Austin.
Please feel free to explore my research and other information across this website! I am more than happy to answer questions and have discussions.
Publications
Tracking Treatment Response via DCE-MRI with an Optimal Temporal Sampling Method
Julie C. DiCarlo, Angela M. Jarrett, Anum S. Kazerouni, John Virostko, Anna G. Sorace, Kalina P. Slavkova, Deborah Patt, Boone Goodgame, Stephanie Woodard, Sarah Avery, Thomas E. Yankeelov
ISMRM Workshop on Perfusion MRI, 2022 Feb
Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting
John Virostko, Anna G. Sorace, Kalina P. Slavkova, Anum S. Kazerouni, Angela M. Jarrett, Julie C. DiCarlo, Stefanie Woodard, Sarah Avery, Boone Goodgame, Debra Patt, Thomas E. Yankeelov
Breast Cancer Research, 2021, p. 110
Kalina P Slavkova, Julie C DiCarlo, Anum K Syed, Chengyue Wu, John Virostko, Anna G Sorace, Thomas E Yankeelov
Cancer Research, vol. 81(4), 2021
Kalina P. Slavkova, Julie C. DiCarlo, Anum S. Kazerouni, John Virostko, Anna G. Sorace, Debra Patt, Boone Goodgame, Thomas E. Yankeelov
Tomography, vol. 7(3), 2021, pp. 253-267
Kalina P. Slavkova, Julie C. DiCarlo, Viraj Wadhwa, Jingfei Ma, Gaiane M. Rauch, Zijian Zhou, Thomas E. Yankeelov, Jonathan I. Tamir
Proc. Intl. Soc. Mag. Reson. Med., Abstract 1448, 2021
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Contact
Kalina Polet Slavkova
PhD Candidate in Physics