activity
20182025
most citedMONAI: An open-source framework for deep learning in healthcare

452 citations · 832 across the 28 of their papers we have counts for

collaborators

28 papers

cs.CV2025

G-SHARP: Gaussian Surgical Hardware Accelerated Real-time Pipeline

Vishwesh Nath, Javier G. Tejero, Aravind S. Kumar +4

We propose G-SHARP, a commercially compatible, real-time surgical scene reconstruction framework designed for minimally invasive procedures that require fast and accurate 3D modeli…

physics.med-ph2024★ 2 cited

MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI

Nancy R. Newlin, Kurt Schilling, Serge Koudoro +33

White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (…

cs.CV2024

A Short Review and Evaluation of SAM2's Performance in 3D CT Image Segmentation

Yufan He, Pengfei Guo, Yucheng Tang +7

Since the release of Segment Anything 2 (SAM2), the medical imaging community has been actively evaluating its performance for 3D medical image segmentation. However, different stu…

eess.IV2024★ 4 cited

HoloHisto: End-to-end Gigapixel WSI Segmentation with 4K Resolution Sequential Tokenization

Yucheng Tang, Yufan He, Vishwesh Nath +11

In digital pathology, the traditional method for deep learning-based image segmentation typically involves a two-stage process: initially segmenting high-resolution whole slide ima…

cs.CV2024★ 6 cited

VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging

Yufan He, Pengfei Guo, Yucheng Tang +11

Foundation models for interactive segmentation in 2D natural images and videos have sparked significant interest in building 3D foundation models for medical imaging. However, the…

cs.CV2024

mTREE: Multi-Level Text-Guided Representation End-to-End Learning for Whole Slide Image Analysis

Quan Liu, Ruining Deng, Can Cui +4

Multi-modal learning adeptly integrates visual and textual data, but its application to histopathology image and text analysis remains challenging, particularly with large, high-re…