Elena Baraznenok

SCALE3D improves prostate cancer risk prediction by analyzing 3D cell interactions through supercell graphs, outperforming traditional features and reducing computational demands.

This paper introduces a 3D microdissection method combining CNC milling and light-sheet microscopy to study tumor evolution in complex 3D structures.

This study evaluates the impact of a 3D pathology workflow on DNA, RNA, and protein integrity, showing minimal effect on amplifiability and transcriptomic profiles.

This paper develops a 3D computational pipeline called SIGHT to detect prostate cancer in pathology datasets using generative immunolabeling, achieving an F1 score comparable to pathologist agreement.

This paper provides an end-to-end workflow for non-destructive 3D pathology using light-sheet microscopy, focusing on fluorescent H&E analogs for preclinical and clinical studies.