activity
20242026
most citedVISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging

6 citations · 16 across the 17 of their papers we have counts for

collaborators

21 papers

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.AI2026

Frozen Models, Evolving Expertise: Model-Agnostic Learning from Deployment Experience for Multimodal Medical AI

Yexiao He, Yucheng Tang, Pengfei Guo +6

Large language models (LLMs) and vision-language models (VLMs) are usually frozen after deployment, so they do not learn from the cases they solve. This is especially concerning in…

cs.AI2026

VERA: Scaling Verifiable Environments for Agentic co-Evolution

Junqi Liu, Yongyang Pan, Zhuosong Jiang +14

Competent agents need precise and verifiable environments, such as sandboxes that are resumable at any stage and evolve from observable evidence. However, most long-horizon work ex…

cs.AI2026

BaT: Towards Self-Evolving Medical Research Agent with Stage Rubrics

Junqi Liu, Yufan He, Yexiao He +9

Long-horizon agents are beginning to automate complete workflows that produce code, reports, and research artifacts. Medical imaging workflows are multi-stage and data-sensitive, w…

cs.AI2026

AutoMedBench: Towards Medical AutoResearch with Agentic AI Models

Junqi Liu, Selena Song, Yuhan Wang +12

Autonomous agents are increasingly expected to support end-to-end medical-AI research workflows, moving beyond isolated prediction tasks or short-form clinical question answering.…

cs.AI2026

Surg: A Spectrum of Large-Scale Multimodal Data and Foundation Models for Surgical Intelligence

Zhitao Zeng, Mengya Xu, Jian Jiang +13

Surgical intelligence has the potential to improve the safety and consistency of surgical care, yet most existing surgical AI frameworks remain task-specific and struggle to genera…

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.RO2026

Humanoid Robots as First Assistants in Endoscopic Surgery

Sue Min Cho, Jan Emily Mangulabnan, Han Zhang +7

Humanoid robots have become a focal point of technological ambition, with claims of surgical capability within years in mainstream discourse. These projections are aspirational yet…

cs.RO2025★ 1 cited

Cosmos-H-Surgical: Learning Surgical Robot Policies from Videos via World Modeling

Yufan He, Pengfei Guo, Mengya Xu +11

Data scarcity remains a fundamental barrier to achieving fully autonomous surgical robots. While large scale vision language action (VLA) models have shown impressive generalizatio…

cs.CV2025

SDUM: A Scalable Deep Unrolled Model for Universal MRI Reconstruction

Puyang Wang, Pengfei Guo, Keyi Chai +3

Clinical MRI encompasses diverse imaging protocols--spanning anatomical targets (cardiac, brain, knee), contrasts (T1, T2, mapping), sampling patterns (Cartesian, radial, spiral, k…

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

Better Tokens for Better 3D: Advancing Vision-Language Modeling in 3D Medical Imaging

Ibrahim Ethem Hamamci, Sezgin Er, Suprosanna Shit +7

Recent progress in vision-language modeling for 3D medical imaging has been fueled by large-scale computed tomography (CT) corpora with paired free-text reports, stronger architect…

eess.IV2025

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction

Niklas Bubeck, Suprosanna Shit, Chen Chen +8

Cardiac Magnetic Resonance (CMR) imaging is a critical tool for diagnosing and managing cardiovascular disease, yet its utility is often limited by the sparse acquisition of 2D sho…

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…

eess.IV2025

Text2CT: Towards 3D CT Volume Generation from Free-text Descriptions Using Diffusion Model

Pengfei Guo, Can Zhao, Dong Yang +9

Generating 3D CT volumes from descriptive free-text inputs presents a transformative opportunity in diagnostics and research. In this paper, we introduce Text2CT, a novel approach…

eess.IV2024

Text-Driven Tumor Synthesis

Xinran Li, Yi Shuai, Chen Liu +11

Tumor synthesis can generate examples that AI often misses or over-detects, improving AI performance by training on these challenging cases. However, existing synthesis methods, wh…

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…

eess.IV2024★ 3 cited

MAISI: Medical AI for Synthetic Imaging

Pengfei Guo, Can Zhao, Dong Yang +8

Medical imaging analysis faces challenges such as data scarcity, high annotation costs, and privacy concerns. This paper introduces the Medical AI for Synthetic Imaging (MAISI), an…

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…