45 citations · 116 across the 92 of their papers we have counts for
26 papers · 2 filters
ProtoFlow: Interpretable and Robust Surgical Workflow Modeling with Learned Dynamic Scene Graph Prototypes
Felix Holm, Ghazal Ghazaei, Nassir Navab
Purpose: Detailed surgical recognition is critical for advancing AI-assisted surgery, yet progress is hampered by high annotation costs, data scarcity, and a lack of interpretable…
LapFM: A Laparoscopic Segmentation Foundation Model via Hierarchical Concept Evolving Pre-training
Qing Xu, Kun Yuan, Yuxiang Luo +4
Surgical segmentation is pivotal for scene understanding yet remains hindered by annotation scarcity and semantic inconsistency across diverse procedures. Existing approaches typic…
From Panel to Pixel: Zoom-In Vision-Language Pretraining from Biomedical Scientific Literature
Kun Yuan, Min Woo Sun, Zhen Chen +7
There is a growing interest in developing strong biomedical vision-language models. A popular approach to achieve robust representations is to use web-scale scientific data. Howeve…
US-X Complete: A Multi-Modal Approach to Anatomical 3D Shape Recovery
Miruna-Alexandra Gafencu, Yordanka Velikova, Nassir Navab +1
Ultrasound offers a radiation-free, cost-effective solution for real-time visualization of spinal landmarks, paraspinal soft tissues and neurovascular structures, making it valuabl…
How Far Are Surgeons from Surgical World Models? A Pilot Study on Zero-shot Surgical Video Generation with Expert Assessment
Zhen Chen, Qing Xu, Jinlin Wu +7
Foundation models in video generation are demonstrating remarkable capabilities as potential world models for simulating the physical world. However, their application in high-stak…
Towards Cellular-Scale Interpretability in Pathology Foundation Models for Biomarker Assessment
Jingsong Liu, Han Li, Zhengyang Xu +19
Molecular biomarker testing in pathology is often costly and tissue-consuming, limiting scalable clinical deployment. Artificial intelligence applied to hematoxylin and eosin (HE)-…
DeepAf: One-Shot Spatiospectral Auto-Focus Model for Digital Pathology
Yousef Yeganeh, Maximilian Frantzen, Michael Lee +3
While Whole Slide Imaging (WSI) scanners remain the gold standard for digitizing pathology samples, their high cost limits accessibility in many healthcare settings. Other low-cost…
BridgeSplat: Bidirectionally Coupled CT and Non-Rigid Gaussian Splatting for Deformable Intraoperative Surgical Navigation
Maximilian Fehrentz, Alexander Winkler, Thomas Heiliger +3
We introduce BridgeSplat, a novel approach for deformable surgical navigation that couples intraoperative 3D reconstruction with preoperative CT data to bridge the gap between surg…
A Fully Open and Generalizable Foundation Model for Ultrasound Clinical Applications
Hongyuan Zhang, Yuheng Wu, Mingyang Zhao +22
Artificial intelligence (AI) that can effectively learn ultrasound representations by integrating multi-source data holds significant promise for advancing clinical care. However,…
UltrON: Ultrasound Occupancy Networks
Magdalena Wysocki, Felix Duelmer, Ananya Bal +2
In free-hand ultrasound imaging, sonographers rely on expertise to mentally integrate partial 2D views into 3D anatomical shapes. Shape reconstruction can assist clinicians in this…
UOPSL: Unpaired OCT Predilection Sites Learning for Fundus Image Diagnosis Augmentation
Zhihao Zhao, Yinzheng Zhao, Junjie Yang +6
Significant advancements in AI-driven multimodal medical image diagnosis have led to substantial improvements in ophthalmic disease identification in recent years. However, acquiri…
CLAPS: A CLIP-Unified Auto-Prompt Segmentation for Multi-Modal Retinal Imaging
Zhihao Zhao, Yinzheng Zhao, Junjie Yang +6
Recent advancements in foundation models, such as the Segment Anything Model (SAM), have significantly impacted medical image segmentation, especially in retinal imaging, where pre…
Decoding the Surgical Scene: A Scoping Review of Scene Graphs in Surgery
Angelo Henriques, Korab Hoxha, Daniel Zapp +3
As surgical AI transitions from pixel-level detection to complex reasoning, Scene Graphs (SGs) offer the structured, relational representations necessary to decode dynamic surgical…
SurgLLM: A Versatile Large Multimodal Model with Spatial Focus and Temporal Awareness for Surgical Video Understanding
Zhen Chen, Xingjian Luo, Kun Yuan +6
Surgical video understanding is crucial for facilitating Computer-Assisted Surgery (CAS) systems. Despite significant progress in existing studies, two major limitations persist, i…
Shape Completion and Real-Time Visualization in Robotic Ultrasound Spine Acquisitions
Miruna-Alexandra Gafencu, Reem Shaban, Yordanka Velikova +2
Ultrasound (US) imaging is increasingly used in spinal procedures due to its real-time, radiation-free capabilities; however, its effectiveness is hindered by shadowing artifacts t…
Recognizing Surgical Phases Anywhere: Few-Shot Test-time Adaptation and Task-graph Guided Refinement
Kun Yuan, Tingxuan Chen, Shi Li +9
The complexity and diversity of surgical workflows, driven by heterogeneous operating room settings, institutional protocols, and anatomical variability, present a significant chal…
CAT-SG: A Large Dynamic Scene Graph Dataset for Fine-Grained Understanding of Cataract Surgery
Felix Holm, Gözde Ünver, Ghazal Ghazaei +1
Understanding the intricate workflows of cataract surgery requires modeling complex interactions between surgical tools, anatomical structures, and procedural techniques. Existing…
HieraSurg: Hierarchy-Aware Diffusion Model for Surgical Video Generation
Diego Biagini, Nassir Navab, Azade Farshad
Surgical Video Synthesis has emerged as a promising research direction following the success of diffusion models in general-domain video generation. Although existing approaches ac…
Temporal Differential Fields for 4D Motion Modeling via Image-to-Video Synthesis
Xin You, Minghui Zhang, Hanxiao Zhang +2
Temporal modeling on regular respiration-induced motions is crucial to image-guided clinical applications. Existing methods cannot simulate temporal motions unless high-dose imagin…
UltraAD: Fine-Grained Ultrasound Anomaly Classification via Few-Shot CLIP Adaptation
Yue Zhou, Yuan Bi, Wenjuan Tong +3
Precise anomaly detection in medical images is critical for clinical decision-making. While recent unsupervised or semi-supervised anomaly detection methods trained on large-scale…
SurgVidLM: Towards Multi-grained Surgical Video Understanding with Large Language Model
Guankun Wang, Junyi Wang, Wenjin Mo +11
Surgical scene understanding is critical for surgical training and robotic decision-making in robot-assisted surgery. Recent advances in Multimodal Large Language Models (MLLMs) ha…
EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding
Ege Özsoy, Arda Mamur, Felix Tristram +4
Operating rooms (ORs) demand precise coordination among surgeons, nurses, and equipment in a fast-paced, occlusion-heavy environment, necessitating advanced perception models to en…
Multimodal Graph Representation Learning for Robust Surgical Workflow Recognition with Adversarial Feature Disentanglement
Long Bai, Boyi Ma, Ruohan Wang +8
Surgical workflow recognition is vital for automating tasks, supporting decision-making, and training novice surgeons, ultimately improving patient safety and standardizing procedu…
Specialized Foundation Models for Intelligent Operating Rooms
Ege Özsoy, Chantal Pellegrini, David Bani-Harouni +3
Surgical procedures unfold in complex environments demanding coordination between surgical teams, tools, imaging and increasingly, intelligent robotic systems. Ensuring safety and…