S. Winfree

A Quantitative Metric of Confidence For Segmentation of Nuclei in Large Spatially Variable Image Volumes

The paper introduces a confidence metric for nuclei segmentation in large spatially variable image volumes, showing it correlates with segmentation quality and F1 scores.

3D Ground Truth Annotations of Nuclei in 3D Microscopy Volumes

The paper provides 3D microscopy volumes with partial manual annotations and synthetically generated volumes for training segmentation methods.

DINAVID: A Distributed and Networked Image Analysis System for Volumetric Image Data

DINAVID provides a cloud-based system for remote 3D microscopy image analysis and visualization, designed to handle large datasets and improve accessibility.

Integrated cytometry with machine learning applied to high-content imaging of human kidney tissue for in-situ cell classification and neighborhood analysis

The paper introduces VTEA, a software tool that integrates machine learning and cytometry analysis for high-content imaging of human kidney tissue to classify cells and analyze their spatial neighborhoods.

The kidney protects against sepsis by producing systemic uromodulin

This paper identifies uromodulin (THP) as a protective factor in sepsis, showing its role in enhancing mononuclear phagocyte function and reducing mortality in mice.

A Multimodal and Integrated Approach to Interrogate Human Kidney Biopsies with Rigor and Reproducibility: The Kidney Precision Medicine Project

The paper describes a pipeline for generating 3D molecular atlases of human kidney biopsies using multi-OMICS and imaging technologies, emphasizing quality control and reproducibility across institutions.

In situ classification of cell types in human kidney tissue using 3D nuclear staining

This paper develops a deep learning method using 3D nuclear staining to classify cell types in human kidney tissue without requiring specific markers.

A precision medicine approach uncovers a unique signature of neutrophils in patients with brushite kidney stones

This study identifies a unique neutrophil signature in brushite kidney stone formers through multi-omics analysis, linking increased neutrophil infiltration and NETosis to tissue scarring and inflammation.