8 citations · 23 across the 26 of their papers we have counts for
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Optimize Surgical Triplet Recognition: A Knowledge-Driven Mixture-of-Experts Solution
Yiyi Zhang, Yuchen Yuan, Ying Zheng +4
Surgical action triplet recognition constitutes a critical task in context-aware robot-assisted surgery, facilitating automatic surgical action perception by identifying instrument…
Attenuation-Resilient Alternating Optimization for Laparoscopic Liver Landmark Detection
Lanqing Liu, Ruize Cui, Jialun Pei +4
Liver surface landmark detection is a fundamental prerequisite for anatomical guidance in laparoscopic liver surgery. However, it remains unreliable in practice due to two pervasiv…
SurgLQA: Scalable Long-Horizon Surgical Video Question Answering
Diandian Guo, Xikai Yang, Ruiyang Li +2
Surgical Video Question Answering (VideoQA) provides a promising paradigm for dynamic intraoperative interpretation, enabling real-time decision support and context-aware retrieval…
Preoperative-to-intraoperative Liver Registration for Laparoscopic Surgery via Latent-Grounded Correspondence Constraints
Ruize Cui, Jialun Pei, Haiqiao Wang +4
In laparoscopic liver surgery, augmented reality technology enhances intraoperative anatomical guidance by overlaying 3D liver models from preoperative CT/MRI onto laparoscopic 2D…
MEJO: MLLM-Engaged Surgical Triplet Recognition via Inter- and Intra-Task Joint Optimization
Yiyi Zhang, Yuchen Yuan, Ying Zheng +4
Surgical triplet recognition, which involves identifying instrument, verb, target, and their combinations, is a complex surgical scene understanding challenge plagued by long-taile…
Topology-Constrained Learning for Efficient Laparoscopic Liver Landmark Detection
Ruize Cui, Jiaan Zhang, Jialun Pei +3
Liver landmarks provide crucial anatomical guidance to the surgeon during laparoscopic liver surgery to minimize surgical risk. However, the tubular structural properties of landma…
Toward Reliable AR-Guided Surgical Navigation: Interactive Deformation Modeling with Data-Driven Biomechanics and Prompts
Zheng Han, Jun Zhou, Jialun Pei +3
In augmented reality (AR)-guided surgical navigation, preoperative organ models are superimposed onto the patient's intraoperative anatomy to visualize critical structures such as…
Benchmarking Endoscopic Surgical Image Restoration and Beyond
Jialun Pei, Diandian Guo, Donghui Yang +5
In endoscopic surgery, a clear and high-quality visual field is critical for surgeons to make accurate intraoperative decisions. However, persistent visual degradation, including s…
U2-BENCH: Benchmarking Large Vision-Language Models on Ultrasound Understanding
Anjie Le, Henan Liu, Yue Wang +18
Ultrasound is a widely-used imaging modality critical to global healthcare, yet its interpretation remains challenging due to its varying image quality on operators, noises, and an…
Landmark-Free Preoperative-to-Intraoperative Registration in Laparoscopic Liver Resection
Jun Zhou, Bingchen Gao, Kai Wang +3
Liver registration by overlaying preoperative 3D models onto intraoperative 2D frames can assist surgeons in perceiving the spatial anatomy of the liver clearly for a higher surgic…
Synergistic Bleeding Region and Point Detection in Laparoscopic Surgical Videos
Jialun Pei, Zhangjun Zhou, Diandian Guo +4
Intraoperative bleeding in laparoscopic surgery causes rapid obscuration of the operative field to hinder the surgical process and increases the risk of postoperative complications…
Rethinking Detecting Salient and Camouflaged Objects in Unconstrained Scenes
Zhangjun Zhou, Yiping Li, Chunlin Zhong +4
While the human visual system employs distinct mechanisms to perceive salient and camouflaged objects, existing models struggle to disentangle these tasks. Specifically, salient ob…
Evaluation Study on SAM 2 for Class-agnostic Instance-level Segmentation
Jialun Pei, Zhangjun Zhou, Tiantian Zhang
Segment Anything Model (SAM) has demonstrated powerful zero-shot segmentation performance in natural scenes. The recently released Segment Anything Model 2 (SAM2) has further heigh…
Surgical Workflow Recognition and Blocking Effectiveness Detection in Laparoscopic Liver Resections with Pringle Maneuver
Diandian Guo, Weixin Si, Zhixi Li +2
Pringle maneuver (PM) in laparoscopic liver resection aims to reduce blood loss and provide a clear surgical view by intermittently blocking blood inflow of the liver, whereas prol…
Depth-Driven Geometric Prompt Learning for Laparoscopic Liver Landmark Detection
Jialun Pei, Ruize Cui, Yaoqian Li +3
Laparoscopic liver surgery poses a complex intraoperative dynamic environment for surgeons, where remains a significant challenge to distinguish critical or even hidden structures…
Tri-modal Confluence with Temporal Dynamics for Scene Graph Generation in Operating Rooms
Diandian Guo, Manxi Lin, Jialun Pei +3
A comprehensive understanding of surgical scenes allows for monitoring of the surgical process, reducing the occurrence of accidents and enhancing efficiency for medical profession…
S^2Former-OR: Single-Stage Bi-Modal Transformer for Scene Graph Generation in OR
Jialun Pei, Diandian Guo, Jingyang Zhang +3
Scene graph generation (SGG) of surgical procedures is crucial in enhancing holistically cognitive intelligence in the operating room (OR). However, previous works have primarily r…
A Unified Query-based Paradigm for Camouflaged Instance Segmentation
Bo Dong, Jialun Pei, Rongrong Gao +3
Due to the high similarity between camouflaged instances and the background, the recently proposed camouflaged instance segmentation (CIS) faces challenges in accurate localization…
Partitioned Saliency Ranking with Dense Pyramid Transformers
Chengxiao Sun, Yan Xu, Jialun Pei +2
In recent years, saliency ranking has emerged as a challenging task focusing on assessing the degree of saliency at instance-level. Being subjective, even humans struggle to identi…
Unite-Divide-Unite: Joint Boosting Trunk and Structure for High-accuracy Dichotomous Image Segmentation
Jialun Pei, Zhangjun Zhou, Yueming Jin +2
High-accuracy Dichotomous Image Segmentation (DIS) aims to pinpoint category-agnostic foreground objects from natural scenes. The main challenge for DIS involves identifying the hi…
CalibNet: Dual-branch Cross-modal Calibration for RGB-D Salient Instance Segmentation
Jialun Pei, Tao Jiang, He Tang +4
We propose a novel approach for RGB-D salient instance segmentation using a dual-branch cross-modal feature calibration architecture called CalibNet. Our method simultaneously cali…
OSFormer: One-Stage Camouflaged Instance Segmentation with Transformers
Jialun Pei, Tianyang Cheng, Deng-Ping Fan +3
We present OSFormer, the first one-stage transformer framework for camouflaged instance segmentation (CIS). OSFormer is based on two key designs. First, we design a location-sensin…
Salient Instance Segmentation via Subitizing and Clustering
Jialun Pei, He Tang, Chao Liu +1
The goal of salient region detection is to identify the regions of an image that attract the most attention. Many methods have achieved state-of-the-art performance levels on this…