Welcome to my personal website!
I graduated with my Ph.D. in Physics in 2022 from the University of Texas at Austin, where I was 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. My dissertation work is titled "Toward advances in data acquisition and analysis for quantitative multi-contrast MRI," consisted of three topics.
Please feel free to explore my research and other information across this website! I am more than happy to answer questions and have discussions.
An untrained deep learning method for reconstructing dynamic magnetic resonance images from accelerated model-based data
Kalina P. Slavkova, Julie C. DiCarlo, Viraj Wadhwa, Chengyue Wu, John Virostko, Sidharth Kumar, Thomas E. Yankeelov, Jonathan I. Tamir
Analysis of Simplicial Complexes to Determine When to Sample for Quantitative DCE-MRI of the Breast.
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
Magnetic Resonance in Medicine (In review), 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, vol. 23, 2021, p. 110
Characterizing errors in perfusion model parameters derived from retrospectively abbreviated quantitative DCE-MRI data
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
Characterizing Errors in Pharmacokinetic Parameters from Analyzing Quantitative Abbreviated DCE-MRI Data in Breast Cancer
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
Characterizing errors in pharmacokinetic parameters from analyzing quantitative abbreviated DCE-MRI data in breast cancer
We compute perfusion parameters from retrospectively abbreviated quantitative DCE-MRI data.
I am a Postdoctoral Researcher at The University of Pennsylvania exploring the intersection of Physics, AI, and cancer imaging.
Kalina Polet Slavkova
3710 Hamilton Walk
Philadelphia, PA 19104