Mitko Veta

This paper develops a method to analyze cancer biomarkers at the nanoscale using single-molecule imaging on clinical liquid biopsies, revealing patient-specific heterogeneity and enabling cancer cell classification.

This study uses third harmonic generation microscopy to image myelin in live human brain tissue, revealing its utility in detecting subtle myelin changes in neurological conditions.

This paper presents a benchmark challenge to compare machine learning models for GABA-edited MRS reconstruction using reduced transients, finding that deep learning models achieve comparable metrics to conventional methods.