5 papers
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…
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…
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…
ProstaTD: Bridging Surgical Triplet from Classification to Fully Supervised Detection
Yiliang Chen, Zhixi Li, Cheng Xu +6
Surgical triplet detection is a critical task in surgical video analysis. However, existing datasets like CholecT50 lack precise spatial bounding box annotations, rendering triplet…
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…