Kalina Polet Slavkova, Ph.D.

Physicist | Computational Oncology + Deep Learning for MRI | Exploring the Intersection of Physics, Biology, & AI

Welcome to my personal website!

As of September 2022, I am a Postdoctoral Researcher in the Department of Radiology at the University of Pennsylvania, advised by Despina Kontos, Ph.D.

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. 
As a Postdoctoral Researcher at Penn, I am continuing to investigate AI for cancer imaging, specifically in the field of radiomics for breast cancer. 

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

arXiv Preprint

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

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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

Postdoctoral Researcher

Department of Radiology

University of Pennsylvania

Goddard Laboratories
3710 Hamilton Walk
Philadelphia, PA 19104