Generation of surgical reports for lymph node dissection during laparoscopic gastric cancer surgery based on artificial intelligence [0.03%]
基于人工智能的腹腔镜胃癌手术淋巴结清扫术手术报告生成研究
Yuhao Zhai,Zhen Chen,Xingjian Luo et al.
Yuhao Zhai et al.
Purpose: This study aimed to develop an artificial intelligence (AI) model for the surgical report output of laparoscopic lymph node dissection in the suprapancreatic region during gastric cancer surgery. ...
Subhadeep Koley,Abdolrahim Kadkhodamohammadi,Santiago Barbarisi et al.
Subhadeep Koley et al.
Purpose: In this paper, we present a novel approach for online object tracking in laparoscopic cholecystectomy (LC) surgical videos, targeting localisation and tracking of critical anatomical structures and instruments. O...
Generating 3D pseudo-healthy knee MR images to support trochleoplasty planning [0.03%]
生成用于支持股骨髁成形术规划的3D假健康膝盖MR图像
Michael Wehrli,Alicia Durrer,Paul Friedrich et al.
Michael Wehrli et al.
Purpose: Trochlear dysplasia (TD) is a common malformation in adolescents, leading to anterior knee pain and instability. Surgical interventions such as trochleoplasty require precise planning to correct the trochlear gro...
Depth-based registration of 3D preoperative models to intraoperative patient anatomy using the HoloLens 2 [0.03%]
基于深度的3D术前模型与术中患者解剖结构的配准研究使用HoloLens 2
Enzo Kerkhof,Abdullah Thabit,Mohamed Benmahdjoub et al.
Enzo Kerkhof et al.
Purpose: In augmented reality (AR) surgical navigation, a registration step is required to align the preoperative data with the patient. This work investigates the use of the depth sensor of HoloLens 2 for registration in...
Thomas De Carvalho,Rawen Kader,Patrick Brandao et al.
Thomas De Carvalho et al.
Purpose: Colorectal cancer is one of the most prevalent cancers worldwide, highlighting the critical need for early and accurate diagnosis to reduce patient risks. Inaccurate diagnoses not only compromise patient outcomes...
Feng Li,Yuan Bi,Dianye Huang et al.
Feng Li et al.
Purpose: The multi-modality imaging system offers optimal fused images for safe and precise interventions in modern clinical practices, such as computed tomography-ultrasound (CT-US) guidance for needle insertion. However...
Automatic diagnosis of abdominal pathologies in untrimmed ultrasound videos [0.03%]
未修剪的超声视频中腹部自动诊断病理条件
Güinther Saibro,Yvonne Keeza,Benoît Sauer et al.
Güinther Saibro et al.
Purpose: Despite major advances in Computer Assisted Diagnosis (CAD), the need for carefully labeled training data remains an important clinical translation barrier. This work aims to overcome this barrier for ultrasound ...
Enhanced self-supervised monocular depth estimation with self-attention and joint depth-pose loss for laparoscopic images [0.03%]
具有自我注意力和联合深度姿态损失的增强自监督单目深度估计在腹腔镜图像中的应用
Wenda Li,Yuichiro Hayashi,Masahiro Oda et al.
Wenda Li et al.
Purpose: Depth estimation is a powerful tool for navigation in laparoscopic surgery. Previous methods utilize predicted depth maps and the relative poses of the camera to accomplish self-supervised depth estimation. Howev...
SfMDiffusion: self-supervised monocular depth estimation in endoscopy based on diffusion models [0.03%]
基于扩散模型的内镜下自助式单目深度估计SfMDiffusion
Yu Li,Da Chang,Die Luo et al.
Yu Li et al.
Purpose: In laparoscopic surgery, accurate 3D reconstruction from endoscopic video is crucial for effective image-guided techniques. Current methods for monocular depth estimation (MDE) face challenges in complex surgical...
Multi-dimensional consistency learning between 2D Swin U-Net and 3D U-Net for intestine segmentation from CT volume [0.03%]
二维Swin U-Net与三维U-Net之间的多维度一致性学习在CT体积上的肠道分割应用研究
Qin An,Hirohisa Oda,Yuichiro Hayashi et al.
Qin An et al.
Purpose: The paper introduces a novel two-step network based on semi-supervised learning for intestine segmentation from CT volumes. The intestine folds in the abdomen with complex spatial structures and contact with neig...