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20212026
most citedMONAI: An open-source framework for deep learning in healthcare

452 citations · 504 across the 25 of their papers we have counts for

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13 papers · 1 filter

cs.CV2026

NV-Generate-Body: 3D Latent Diffusion Model forControllable Anatomy, Tumor, and Demographic Body Mask Synthesis

Can Zhao, Pengfei Guo, Dong Yang +8

Curating large labeled CT datasets is expensive and constrained by patient privacy. We present NV-Generate-BodyMask, a 3D latent diffusion model that synthesizes whole-body CT segm…

cs.CV2026

Cosmos 3: Omnimodal World Models for Physical AI

NVIDIA, :, Aditi +293

We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…

cs.CV2026

SAW: Toward a Surgical Action World Model via Controllable and Scalable Video Generation

Sampath Rapuri, Lalithkumar Seenivasan, Dominik Schneider +9

A surgical world model capable of generating realistic surgical action videos with precise control over tool-tissue interactions can address fundamental challenges in surgical AI a…

cs.CV2025

Reasoning Visual Language Model for Chest X-Ray Analysis

Andriy Myronenko, Dong Yang, Baris Turkbey +10

Vision-language models (VLMs) have shown strong promise for medical image analysis, but most remain opaque, offering predictions without the transparent, stepwise reasoning clinici…

cs.CV2025

Auto3DSeg for Brain Tumor Segmentation from 3D MRI in BraTS 2023 Challenge

Andriy Myronenko, Dong Yang, Yufan He +1

In this work, we describe our solution to the BraTS 2023 cluster of challenges using Auto3DSeg from MONAI. We participated in all 5 segmentation challenges, and achieved the 1st pl…

cs.CV2025

Towards the Automatic Segmentation, Modeling and Meshing of the Aortic Vessel Tree from Multicenter Acquisitions: An Overview of the SEG.A. 2023 Segmentation of the Aorta Challenge

Yuan Jin, Antonio Pepe, Gian Marco Melito +36

The automated analysis of the aortic vessel tree (AVT) from computed tomography angiography (CTA) holds immense clinical potential, but its development has been impeded by a lack o…

cs.CV2025★ 1 cited

MAISI-v2: Accelerated 3D High-Resolution Medical Image Synthesis with Rectified Flow and Region-specific Contrastive Loss

Can Zhao, Pengfei Guo, Dong Yang +7

Medical image synthesis is an important topic for both clinical and research applications. Recently, diffusion models have become a leading approach in this area. Despite their str…

cs.CV2024★ 1 cited

VILA-M3: Enhancing Vision-Language Models with Medical Expert Knowledge

Vishwesh Nath, Wenqi Li, Dong Yang +22

Generalist vision language models (VLMs) have made significant strides in computer vision, but they fall short in specialized fields like healthcare, where expert knowledge is esse…

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…

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.CV2023★ 3 cited

Automated 3D Segmentation of Kidneys and Tumors in MICCAI KiTS 2023 Challenge

Andriy Myronenko, Dong Yang, Yufan He +1

Kidney and Kidney Tumor Segmentation Challenge (KiTS) 2023 offers a platform for researchers to compare their solutions to segmentation from 3D CT. In this work, we describe our su…

cs.CV2023★ 5 cited

Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training

Jeya Maria Jose Valanarasu, Yucheng Tang, Dong Yang +8

Harnessing the power of pre-training on large-scale datasets like ImageNet forms a fundamental building block for the progress of representation learning-driven solutions in comput…

cs.CV2021★ 20 cited

DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation

Yufan He, Dong Yang, Holger Roth +2

Recently, neural architecture search (NAS) has been applied to automatically search high-performance networks for medical image segmentation. The NAS search space usually contains…