1 citations · 3 across the 14 of their papers we have counts for
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From Articulated Kinematics to Routed Visual Control for Action-Conditioned Surgical Video Generation
Bohan Li, Shuojue Yang, Baorui Peng +10
Action-conditioned surgical video generation is a critical yet highly challenging problem for robotic surgery. The core difficulty is that low-dimensional control vectors must prec…
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…
Generalized Recognition of Basic Surgical Actions Enables Skill Assessment and Vision-Language-Model-based Surgical Planning
Mengya Xu, Daiyun Shen, Jie Zhang +19
Artificial intelligence, imaging, and large language models have the potential to transform surgical practice, training, and automation. Understanding and modeling of basic surgica…
Surg-R1: A Hierarchical Reasoning Foundation Model for Scalable and Interpretable Surgical Decision Support with Multi-Center Clinical Validation
Jian Jiang, Chenxi Lin, Yiming Gu +24
Surgical scene understanding demands not only accurate predictions but also interpretable reasoning that surgeons can verify against clinical expertise. However, existing surgical…
MedOpenClaw and MedFlowBench: Auditing Medical Agents in Full-Study Workflows
Weixiang Shen, Chengzhi Shen, Yanzhu Hu +12
Medical imaging benchmarks often evaluate VLMs on pre-selected 2D images, slices, crops, or patches, making evaluation closer to visual recognition. Real clinical workflows impose…
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…
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…
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…
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…
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…
NVILA: Efficient Frontier Visual Language Models
Zhijian Liu, Ligeng Zhu, Baifeng Shi +24
Visual language models (VLMs) have made significant advances in accuracy in recent years. However, their efficiency has received much less attention. This paper introduces NVILA, a…