2 citations · 4 across the 13 of their papers we have counts for
9 papers · 1 filter
Dense Structural Priors for Sparse Functional Landmark Localization in Surgical Videos
Chenyan Jing, Hao Ding, Lalithkumar Seenivasan +2
Vision foundation models such as SAM 3 can provide transferable object-level structure across diverse surgical video conditions, but segmentation outputs do not explicitly encode t…
TikArt: Stabilizing Aperture-Guided Fine-Grained Visual Reasoning with Reinforcement Learning
Hao Ding, Zhichuan Yang, Weijie Ge +3
Fine-grained visual reasoning in multimodal large language models (MLLMs) is bottlenecked by single-pass global image encoding: key evidence often lies in tiny objects, cluttered r…
BronchOpt : Vision-Based Pose Optimization with Fine-Tuned Foundation Models for Accurate Bronchoscopy Navigation
Hongchao Shu, Roger D. Soberanis-Mukul, Jiru Xu +6
Accurate intra-operative localization of the bronchoscope tip relative to patient anatomy remains challenging due to respiratory motion, anatomical variability, and CT-to-body dive…
Egosurg: Arbitrary view synthesis for egocentric replay of operating room workflows from ambient cameras
Han Zhang, Lalithkumar Seenivasan, Jose L. Porras +10
Observing surgical practice has historically relied on fixed vantage points or recollections, leaving the egocentric perspectives that shape clinical decisions undocumented. Ambien…
Endo3R: Unified Online Reconstruction from Dynamic Monocular Endoscopic Video
Jiaxin Guo, Wenzhen Dong, Tianyu Huang +5
Reconstructing 3D scenes from monocular surgical videos can enhance surgeon's perception and therefore plays a vital role in various computer-assisted surgery tasks. However, achie…
UINO-FSS: Unifying Representation Learning and Few-shot Segmentation via Hierarchical Distillation and Mamba-HyperCorrelation
Wei Zhuo, Zhiyue Tang, Wufeng Xue +3
Few-shot semantic segmentation has attracted growing interest for its ability to generalize to novel object categories using only a few annotated samples. To address data scarcity,…
MoSFormer: Augmenting Temporal Context with Memory of Surgery for Surgical Phase Recognition
Hao Ding, Xu Lian, Mathias Unberath
Surgical phase recognition from video enables various downstream applications. Transformer-based sliding window approaches have set the state-of-the-art by capturing rich spatial-t…
Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin Representation
Hao Ding, Yuqian Zhang, Wenzheng Cheng +7
Surgical phase recognition (SPR) is an integral component of surgical data science, enabling high-level surgical analysis. End-to-end trained neural networks that predict surgical…
SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge
Hao Ding, Yuqian Zhang, Tuxun Lu +39
Surgical data science has seen rapid advancement with the excellent performance of end-to-end deep neural networks (DNNs). Despite their successes, DNNs have been proven susceptibl…