Valentina Matos-Romero

The paper quantifies PanIN burden and pancreatic composition across age to identify high-risk demographics associated with increased precancer burden.

TiSAM improves whole-slide image segmentation by fusing spatial and histopathology features, achieving high accuracy across diverse datasets and scanners.

CODAvision provides a user-friendly interface for rapid, customizable medical image segmentation using deep learning, enabling non-experts to train and evaluate models across diverse imaging modalities.

The paper investigates muscle loss as a key evolutionary step in turtle shell development using multi-modal imaging and histology-based deep learning to analyze turtle embryos.

PIVOT is an open-source tool for nonlinear registration of multi-omic spatial data, demonstrating improved throughput compared to existing workflows.

This study shows that 3D assessments are necessary to accurately determine tissue composition and neoplastic content, as 2D methods under-sample spatial heterogeneity.