154 citations · 242 across the 10 of their papers we have counts for
10 papers
Evaluating Usability in Biomedical Visualization: Rethinking Heuristic Evaluation for Spatial Omics and Multidisciplinary Research Platforms
Yulia A. Levites Strekalova, Rachel Liu Galvin, Jessica M. Ray +11
Introduction: Clinical research informatics (CRI) platforms support biomedical discovery by integrating advanced computational tools into research workflows. Emerging technologies…
A Comprehensive Benchmark of Histopathology Foundation Models for Kidney Digital Pathology Images
Harishwar Reddy Kasireddy, Patricio S. La Rosa, Akshita Gupta +12
Histopathology foundation models (HFMs), pretrained on large-scale cancer datasets, have advanced computational pathology. However, their applicability to non-cancerous chronic kid…
Interactive visualization of kidney micro-compartmental segmentations and associated pathomics on whole slide images
Mark S. Keller, Nicholas Lucarelli, Yijiang Chen +13
Application of machine learning techniques enables segmentation of functional tissue units in histology whole-slide images (WSIs). We built a pipeline to apply previously validated…
PathDiff: Histopathology Image Synthesis with Unpaired Text and Mask Conditions
Mahesh Bhosale, Abdul Wasi, Yuanhao Zhai +7
Diffusion-based generative models have shown promise in synthesizing histopathology images to address data scarcity caused by privacy constraints. Diagnostic text reports provide h…
CASC-AI: Consensus-aware Self-corrective Learning for Noise Cell Segmentation
Ruining Deng, Yihe Yang, David J. Pisapia +15
Multi-class cell segmentation in high-resolution gigapixel whole slide images (WSIs) is crucial for various clinical applications. However, training such models typically requires…
Histo-fetch -- On-the-fly processing of gigapixel whole slide images simplifies and speeds neural network training
Brendon Lutnick, Leema Krishna Murali, Brandon Ginley +2
We created a custom pipeline (histo-fetch) to efficiently extract random patches and labels from pathology whole slide images (WSIs) for input to a neural network on-the-fly. We pr…
Neural Network Segmentation of Interstitial Fibrosis, Tubular Atrophy, and Glomerulosclerosis in Renal Biopsies
Brandon Ginley, Kuang-Yu Jen, Avi Rosenberg +4
Glomerulosclerosis, interstitial fibrosis, and tubular atrophy (IFTA) are histologic indicators of irrecoverable kidney injury. In standard clinical practice, the renal pathologist…
Unsupervised Community Detection with a Potts Model Hamiltonian, an Efficient Algorithmic Solution, and Applications in Digital Pathology
Brendon Lutnick, Wen Dong, Zohar Nussinov +1
Unsupervised segmentation of large images using a Potts model Hamiltonian is unique in that segmentation is governed by a resolution parameter which scales the sensitivity to small…
Iterative annotation to ease neural network training: Specialized machine learning in medical image analysis
Brendon Lutnick, Brandon Ginley, Darshana Govind +7
Neural networks promise to bring robust, quantitative analysis to medical fields, but adoption is limited by the technicalities of training these networks. To address this translat…
Multi-radial LBP Features as a Tool for Rapid Glomerular Detection and Assessment in Whole Slide Histopathology Images
Olivier Simon, Rabi Yacoub, Sanjay Jain +1
We demonstrate a simple and effective automated method for the segmentation of glomeruli from large (~1 gigapixel) histopathological whole-slide images (WSIs) of thin renal tissue…