Lucie Dequiedt

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.

This paper introduces SMILE, a diffusion model for converting H&E stains to multiplex IHC images, showing superior performance in pancreatic islet analysis and breast cancer stain conversion.

The paper uses 3D imaging to analyze vascular and nervous systems in embryos, finding shared structural principles but distinct architectures shaped by biophysical constraints.

This study uses spatial multi-omics to identify TLS-associated immune niches in PDAC that correlate with improved survival in immunotherapy responders.

The paper profiles the immune microenvironment of PanINs in 3D at single-cell resolution to understand inflammation's role in cancer progression and finds immune heterogeneity and correlations with PanIN grade.

This paper uses deep learning to label 17 kidney microstructures in 3D fetal rhesus macaque kidneys, revealing spatial relationships between glomeruli, arteries, and nephrons.