We have developed PodoCount, an automated tool for podocyte detection and three-dimensional quantification from histologic sections of renal tissue biopsy whole slide images (WSIs) with podocytes labeled using immunohistochemistry labels.
We have developed PodoSighter, a cloud-based tool for automated, label-free podocyte detection and three-dimensional quantification from periodic acid-Schiff-stained histologic sections of renal tissue biopsy WSIs.
A machine learning (ML) pipeline is developed to conduct reliable, digital, and automated detection of interstitial fibrosis and tubular atrophy (IFTA).
We developed a digital pipeline to classify renal biopsies from patients with diabetic nephropathy (DN). We combined traditional image analysis with modern machine learning to efficiently capture important structures, minimize manual effort and supervision, and enforce biologic prior information onto our model.
We have developed a supervised computational pipeline to detect glomeruli from digital renal biopsy WSIs.
We have developed an unsupervised automated quantification of glomerulus from digital renal biopsy WSIs.