activity
20192025
most citedMONAI: An open-source framework for deep learning in healthcare

452 citations · 538 across the 21 of their papers we have counts for

collaborators

26 papers

cs.CV2025

KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level

Ruining Deng, Tianyuan Yao, Yucheng Tang +44

Chronic kidney disease (CKD) is a major global health issue, affecting over 10% of the population and causing significant mortality. While kidney biopsy remains the gold standard f…

cs.CV2025

Post-Training Quantization for 3D Medical Image Segmentation: A Practical Study on Real Inference Engines

Chongyu Qu, Ritchie Zhao, Ye Yu +6

Quantizing deep neural networks ,reducing the precision (bit-width) of their computations, can remarkably decrease memory usage and accelerate processing, making these models more…

cs.LG2022452 cited

MONAI: An open-source framework for deep learning in healthcare

M. Jorge Cardoso, Wenqi Li, Richard Brown +53

Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagn…

cs.CV2022

Adaptive Contrastive Learning with Dynamic Correlation for Multi-Phase Organ Segmentation

Ho Hin Lee, Yucheng Tang, Han Liu +7

Recent studies have demonstrated the superior performance of introducing ``scan-wise" contrast labels into contrastive learning for multi-organ segmentation on multi-phase computed…

eess.IV20224 cited

Reducing Positional Variance in Cross-sectional Abdominal CT Slices with Deep Conditional Generative Models

Xin Yu, Qi Yang, Yucheng Tang +8

2D low-dose single-slice abdominal computed tomography (CT) slice enables direct measurements of body composition, which are critical to quantitatively characterizing health relati…

cs.CV2022

Longitudinal Variability Analysis on Low-dose Abdominal CT with Deep Learning-based Segmentation

Xin Yu, Yucheng Tang, Qi Yang +6

Metabolic health is increasingly implicated as a risk factor across conditions from cardiology to neurology, and efficiency assessment of body composition is critical to quantitati…