- Automated glioma multiclass tumor classification
- Style transfer between microscopy and magnetic resonance imaging via generative adversarial network in small sample size settings
- Deep Learning Glioma Grading with the Tumor Microenvironment Analysis Protocol for Comprehensive Learning, Discovering, and Quantifying Microenvironmental Features
Research / Computer Vision (Computational Neuroscience)
Monika Pytlarz
PhD Student in Computer Vision (Computational Neuroscience)
Monika obtained a BSc in Electroradiology from Collegium Medicum of the Jagiellonian University and an MSc in Bioinformatics from JU. During her master’s studies, she was involved in the development of an algorithm for the automatic segmentation of a high-resolution ultrasound image. She has experience working with clinical patients in the hospital Diagnostic Imaging Department as a radiographer. In Sano, she investigates the use of generative adversarial networks to generate data in the context of microscopy. In her free time, she dances pole art, enjoys alternative music concerts, and plays analog RPGs.