The Experts below are selected from a list of 18894 Experts worldwide ranked by ideXlab platform
Max Q.-h. Meng - One of the best experts on this subject based on the ideXlab platform.
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ICIA - Robot-assisted occlusion avoidance for Surgical Instrument optical tracking system
2015 IEEE International Conference on Information and Automation, 2015Co-Authors: Jiaole Wang, Lin Qi, Max Q.-h. MengAbstract:Due to the direct line-of-sight constraint, Surgical Instrument optical tracking system (OTS) suffers occlusion problem caused by the equipments, staff members, or Surgical Instruments during the operation. To alleviate the burden of surgeons, we propose a robotic platform and an optimization based control methods to autonomously re-configure the optical tracker when the occlusion problem is about to occur. The robotic platform, which comprises a robot arm with 4 degrees of freedom, an optical tracker, and a RGB-D camera, is first proposed and characterized. The problem formulation and algorithm development are then intensively analysed. Furthermore, simulation experiments with different occlusion situations are conducted. The results are analyzed and discussed in the end.
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towards occlusion free Surgical Instrument tracking a modular monocular approach and an agile calibration method
IEEE Transactions on Automation Science and Engineering, 2015Co-Authors: Jiaole Wang, Max Q.-h. MengAbstract:Optical means of Instrument tracking has been widely used in image-guided interventions and considered the de facto standard for tracking rigid bodies with a direct line-of-sight. However, the occlusion problem which remains unresolved in current systems frustrates surgeons during the operation. To address this challenge, we propose a Surgical Instrument tracking system based on multiple reconfigurable monocular modules. The main approach is to enable the system to dynamically reconfigure the multiple monocular modules when occlusion occurs partially within the workspace. In this paper, we focus on the system architecture and an agile multicamera calibration method which only uses the customized tool for the Surgical Instrument tracking scenario. Additionally, two fast non-iterative algorithms are proposed and studied. In order to show the feasibility and superiority of the corresponding multicamera calibration algorithm, comparison experiments have carried out. The intensive investigation results give a practical instruction to the real implementation of the proposed system in image-guided interventions.
Jiaole Wang - One of the best experts on this subject based on the ideXlab platform.
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ICIA - Robot-assisted occlusion avoidance for Surgical Instrument optical tracking system
2015 IEEE International Conference on Information and Automation, 2015Co-Authors: Jiaole Wang, Lin Qi, Max Q.-h. MengAbstract:Due to the direct line-of-sight constraint, Surgical Instrument optical tracking system (OTS) suffers occlusion problem caused by the equipments, staff members, or Surgical Instruments during the operation. To alleviate the burden of surgeons, we propose a robotic platform and an optimization based control methods to autonomously re-configure the optical tracker when the occlusion problem is about to occur. The robotic platform, which comprises a robot arm with 4 degrees of freedom, an optical tracker, and a RGB-D camera, is first proposed and characterized. The problem formulation and algorithm development are then intensively analysed. Furthermore, simulation experiments with different occlusion situations are conducted. The results are analyzed and discussed in the end.
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towards occlusion free Surgical Instrument tracking a modular monocular approach and an agile calibration method
IEEE Transactions on Automation Science and Engineering, 2015Co-Authors: Jiaole Wang, Max Q.-h. MengAbstract:Optical means of Instrument tracking has been widely used in image-guided interventions and considered the de facto standard for tracking rigid bodies with a direct line-of-sight. However, the occlusion problem which remains unresolved in current systems frustrates surgeons during the operation. To address this challenge, we propose a Surgical Instrument tracking system based on multiple reconfigurable monocular modules. The main approach is to enable the system to dynamically reconfigure the multiple monocular modules when occlusion occurs partially within the workspace. In this paper, we focus on the system architecture and an agile multicamera calibration method which only uses the customized tool for the Surgical Instrument tracking scenario. Additionally, two fast non-iterative algorithms are proposed and studied. In order to show the feasibility and superiority of the corresponding multicamera calibration algorithm, comparison experiments have carried out. The intensive investigation results give a practical instruction to the real implementation of the proposed system in image-guided interventions.
Yoshihiro Kakeji - One of the best experts on this subject based on the ideXlab platform.
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automated Surgical Instrument detection from laparoscopic gastrectomy video images using an open source convolutional neural network platform
Journal of The American College of Surgeons, 2020Co-Authors: Yuta Yamazaki, Shingo Kanaji, Takeru Matsuda, Taro Oshikiri, Tetsu Nakamura, Satoshi Suzuki, Yuta Hiasa, Yoshito Otake, Yoshinobu Sato, Yoshihiro KakejiAbstract:Background The common use of laparoscopic intervention produces impressive amounts of video data that are difficult to review for surgeons wishing to evaluate and improve their skills. Therefore, a need exists for the development of computer-based analysis of laparoscopic video to accelerate Surgical training and assessment. We developed a Surgical Instrument detection system for video recordings of laparoscopic gastrectomy procedures. This system, the use of which might increase the efficiency of the video reviewing process, is based on the open source neural network platform, YOLOv3. Study Design A total of 10,716 images extracted from 52 laparoscopic gastrectomy videos were included in the training and validation data sets. We performed 200,000 iterations of training. Video recordings of 10 laparoscopic gastrectomies, independent of the training and validation data set, were analyzed by our system, and heat maps visualizing trends of Surgical Instrument usage were drawn. Three skilled surgeons evaluated whether each heat map represented the features of the corresponding operation. Results After training, the testing data set precision and sensitivity (recall) was 0.87 and 0.83, respectively. The heat maps perfectly represented the devices used during each operation. Without reviewing the video recordings, the surgeons accurately recognized the type of anastomosis, time taken to initiate duodenal and gastric dissection, and whether any irregular procedure was performed, from the heat maps (correct answer rates ≥ 90%). Conclusions A new automated system to detect manipulation of Surgical Instruments in video recordings of laparoscopic gastrectomies based on the open source neural network platform, YOLOv3, was developed and validated successfully.
Pierre Jannin - One of the best experts on this subject based on the ideXlab platform.
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vision based and marker less Surgical tool detection and tracking a review of the literature
Medical Image Analysis, 2017Co-Authors: David Bouget, Max Allan, Danail Stoyanov, Pierre JanninAbstract:In recent years, tremendous progress has been made in Surgical practice for example with Minimally Invasive Surgery (MIS). To overcome challenges coming from deported eye-to-hand manipulation, robotic and computer-assisted systems have been developed. Having real-time knowledge of the pose of Surgical tools with respect to the Surgical camera and underlying anatomy is a key ingredient for such systems. In this paper, we present a review of the literature dealing with vision-based and marker-less Surgical tool detection. This paper includes three primary contributions: (1) identification and analysis of data-sets used for developing and testing detection algorithms, (2) in-depth comparison of Surgical tool detection methods from the feature extraction process to the model learning strategy and highlight existing shortcomings, and (3) analysis of validation techniques employed to obtain detection performance results and establish comparison between Surgical tool detectors. The papers included in the review were selected through PubMed and Google Scholar searches using the keywords: “Surgical tool detection”, “Surgical tool tracking”, “Surgical Instrument detection” and “Surgical Instrument tracking” limiting results to the year range 2000 2015. Our study shows that despite significant progress over the years, the lack of established Surgical tool data-sets, and reference format for performance assessment and method ranking is preventing faster improvement.
Gordon F West - One of the best experts on this subject based on the ideXlab platform.
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assessment of Surgical Instrument bioburden after steam sterilization a pilot study
American Journal of Infection Control, 2020Co-Authors: Marisol Resendiz, Timothy S Horseman, Andrew J Hover, David F Bradley, Michael B Lustik, Gordon F WestAbstract:In environments in which manual decontamination and steam sterilization remains the primary method of sterilization, biofilm formation can increase the risk of disease transmission. To determine the risk of bacterial survival and contamination on Surgical Instruments, inoculated blood was dried on one Instrument and steam sterilized (wrapped or unwrapped) in a set of 4 (including 3 clean). Two of 3 pathogens were recovered at a rate of 15% for unwrapped sets and 33% for wrapped sets.
