Adaptive sensitivity-fisher regularization for heterogeneous transfer learning of vascular segmentation in laparoscopic videos [0.03%]
自适应敏感性-Fisher正则化在腹腔镜视频血管分割中的异构迁移学习中的应用
Xinkai Zhao,Yuichiro Hayashi,Masahiro Oda et al.
Xinkai Zhao et al.
Purpose: This study aims to enhance surgical safety by developing a method for vascular segmentation in laparoscopic surgery videos with limited visibility. We introduce an adaptive sensitivity-fisher regularization (ASFR...
Application of a "4-steps" approach for management of Henle's Trunk in right hemicolectomy [0.03%]
右半结肠切除术中亨勒干的应用及"四步"操作法
Yihang Wu,Feiyu Bai,Xiaojian Wu et al.
Yihang Wu et al.
Methods: We retrospectively analyzed laparoscopic videos of the right hemicolectomy for Henle's Trunk, and classified the key procedure steps into the four steps.
Intraoperative patient-specific volumetric reconstruction and 3D visualization for laparoscopic liver surgery [0.03%]
腹腔镜肝手术中基于个体的术中体积重建和三维可视化技术
Luca Boretto,Egidijus Pelanis,Alois Regensburger et al.
Luca Boretto et al.
The technique combines neural radiance field reconstructions from tracked laparoscopic videos with ultrasound three-dimensional compounding.
Neural fields for 3D tracking of anatomy and surgical instruments in monocular laparoscopic video clips [0.03%]
基于单目腹腔镜视频片段的神经网络场及其在解剖结构和手术器械三维定位中的应用
Beerend G A Gerats,Jelmer M Wolterink,Seb P Mol et al.
Beerend G A Gerats et al.
On laparoscopic videos in the SCARED dataset, the method predicts depth with an MAE of 2.9 mm and a relative error of 9.2%. These results show the feasibility of using neural fields for monocular 3D reconstruction of laparoscopic scenes.
The impact of short-course total neoadjuvant therapy, long-course chemoradiotherapy, and upfront surgery on the technical difficulty of total mesorectal excision: an observational study with an intraoperative perspective [0.03%]
短程新辅助治疗、长程放化疗和早期手术对全直肠系膜切除术技术难度的影响：一项基于术中情况的观察性研究
Cheryl Xi-Zi Chong,Frederick H Koh,Hui-Lin Tan et al.
Cheryl Xi-Zi Chong et al.
Methods: Twelve laparoscopic videos of low anterior resection with TME for rectal cancer were prospectively collected from January 2020 to October 2021, with 4 videos in each arm.
SeeSaw: Learning Soft Tissue Deformation from Laparoscopy Videos with GNNs [0.03%]
基于图神经网络的腹腔镜手术软组织形变预测方法研究
Reuben Docea,Jinjing Xu,Wei Ling et al.
Reuben Docea et al.
Our innovative approach learns to compensate non-rigidity in abdominal endoscopic scenes directly from stereo laparoscopic videos through targeting a new problem formulation, and stands to benefit a variety of target applications in dynamic environments.
Anastomotic tension "Bridging": a risk factor for anastomotic leakage following low anterior resection [0.03%]
吻合张力"桥接"：低位前切术术后吻合口漏的风险因素
Ryogo Ito,Hideo Matsubara,Ryoichi Shimizu et al.
Ryogo Ito et al.
Methods: This retrospective study reviewed the medical records and laparoscopic videos of 102 patients who underwent laparoscopic LAR using the double stapling technique at Yachiyo Hospital between January 2014 and December 2023.
Prediction of remaining surgery duration in laparoscopic videos based on visual saliency and the transformer network [0.03%]
基于视觉显著性和变压器网络的腹腔镜视频剩余手术时间预测
Constantinos Loukas,Ioannis Seimenis,Konstantina Prevezanou et al.
Constantinos Loukas et al.
Background: Real-time prediction of the remaining surgery duration (RSD) is important for optimal scheduling of resources in the operating room. Methods: ...
Dual-correlate optimized coarse-fine strategy for monocular laparoscopic videos feature matching via multilevel sequential coupling feature descriptor [0.03%]
通过多级顺序耦合特征描述符进行单目腹腔镜视频特征匹配的双相关优化粗细策略
Ziang Zhang,Hong Song,Jingfan Fan et al.
Ziang Zhang et al.
Feature matching of monocular laparoscopic videos is crucial for visualization enhancement in computer-assisted surgery, and the keys to conducting high-quality matches are accurate homography estimation, relative pose estimation, as well as sufficient matches and fast calculation.
Development of a deep learning model for safe direct optical trocar insertion in minimally invasive surgery: an innovative method to prevent trocar injuries [0.03%]
微创手术安全直接光学套管插入的深度学习模型开发：防止套管损伤的一种创新方法
Supakool Jearanai,Piyanun Wangkulangkul,Wannipa Sae-Lim et al.
Supakool Jearanai et al.
The model was trained on still images and inferenced on laparoscopic videos to ensure real-time detection in the operating room. The alarm system was activated upon recognizing the peritoneum and abdominal cavity layers.
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