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Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks [article]

Amy Jin, Serena Yeung, Jeffrey Jopling, Jonathan Krause, Dan Azagury, Arnold Milstein, Li Fei-Fei
2018 arXiv   pre-print
In this work, we introduce an approach to automatically assess surgeon performance by tracking and analyzing tool movements in surgical videos, leveraging region-based convolutional neural networks.  ...  To do this, it is essential to assess operative skill, a process that currently requires experts and is manual, time consuming, and subjective.  ...  Our work builds on these prior contributions and uses region-based convolutional neural networks [25] to detect the spatial bounds of tools, enabling richer, more comprehensive assessment of surgical  ... 
arXiv:1802.08774v2 fatcat:zbchxdooivgmvn5qkeng4xk2v4

Video-based assessment of intraoperative surgical skill [article]

Sanchit Hira, Digvijay Singh, Tae Soo Kim, Shobhit Gupta, Gregory Hager, Shameema Sikder, S. Swaroop Vedula
2022 arXiv   pre-print
In the first method, we predict instrument tips as keypoints, and learn surgical skill using temporal convolutional neural networks.  ...  Conclusion: Deep learning methods are necessary for video-based assessment of surgical skill in the operating room.  ...  detect such patterns in an end-to-end manner using a convolutional neural network.  ... 
arXiv:2205.06416v1 fatcat:harc6quoibcpji3dzibl6c5iwq

Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection

Duygu Sarikaya, Jason J. Corso, Khurshid A. Guru
2017 IEEE Transactions on Medical Imaging  
We propose an architecture using multimodal convolutional neural networks for fast detection and localization of tools in RAS videos.  ...  To our knowledge, this approach will be the first to incorporate deep neural networks for tool detection and localization in RAS videos.  ...  We use the Caffe framework by Jia et al. [39] for our experiments and the optical flow estimation code by Brox et al. [40] , for estimating the temporal motion cues between video frames.  ... 
doi:10.1109/tmi.2017.2665671 pmid:28186883 fatcat:dqwdwcpevvey7dzgprjlz2osem

Box-Trainer Assessment System with Real-Time Multi-Class Detection and Tracking of Laparoscopic Instruments, using CNN

Fatemeh Rashidi Fathabadi, Janos L. Grantner, Ikhlas Abdel-Qader, Saad A. Shebrain
2022 Acta Polytechnica Hungarica  
In this paper, we propose real-time detection and tracking of a multi-class of laparoscopic instruments for an intelligent box-trainer performance assessment system using SSD-ResNet50 V1 FPN architecture  ...  Video recording of residents' performance and computerassisted surgical trainers for MIS provide valuable information for resident's assessment.  ...  School of Medicine, WMU (Contract #: 29-7023660), and the Office of Vice President for Research (OVPR), WMU (Project #: 161, 2018-19). We gratefully thank Mr. Hossein Rahmatpour  ... 
doi:10.12700/aph.19.2.2022.2.1 fatcat:c7cplnh5kzd55jtrbujyhmdigm

Real-time Surgical Tools Recognition in Total Knee Arthroplasty Using Deep Neural Networks [article]

Moazzem Hossain, Soichi Nishio, Takafumi Hiranaka, Syoji Kobashi
2018 arXiv   pre-print
Therefore, this research proposes the development of a real-time system for the recognition of surgical tools during surgery using a convolutional neural network (CNN).  ...  Also, the presence and movement of tools in surgery are crucial information for the recognition of the operational phase and to identify the surgical workflow.  ...  Our work builds on these prior contributions and uses region-based convolutional neural networks to detect the spatial bounds of tools, enabling more affluent and comprehensive assessment of surgical quality  ... 
arXiv:1806.02031v1 fatcat:jxknxgt3rba5zkr3wkxyfe4pea

Surgical Tools Detection Based on Modulated Anchoring Network in Laparoscopic Videos

Beibei Zhang, Shengsheng Wang, Liyan Dong, Peng Chen
2020 IEEE Access  
INDEX TERMS Laparoscopic surgery, tool detection, convolutional neural network, operational quality assessment.  ...  Detection of surgical tools with more accurate spatial locations in surgical videos not only helps to ensure patient safety by reducing the incidence of complications but also makes a difference to assess  ...  Thus, we propose a detection network to locate surgical tools accurately for automated surgical video analysis in real-time to assess performance faster and better.  ... 
doi:10.1109/access.2020.2969885 fatcat:d5hnuplpzfaypbfxk22psqa35i

Deep Neural Networks for the Assessment of Surgical Skills: A Systematic Review [article]

Erim Yanik, Xavier Intes, Uwe Kruger, Pingkun Yan, David Miller, Brian Van Voorst, Basiel Makled, Jack Norfleet, Suvranu De
2021 arXiv   pre-print
Based on this review, we concluded that DNNs are powerful tools for automated, objective surgical skill assessment using both kinematic and video data.  ...  Here, we use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to systematically survey the literature on the use of Deep Neural Networks for automated and objective  ...  C C R & C C TCN: Temporal Convolutional Neural Network, RCNN: Region-Based Convolutional Neural Network SFR: Statistical Feature Representation R: Regression, C: Classification  ... 
arXiv:2103.05113v1 fatcat:wdimnvsqdrcrpmzlaj3afpxwmm

Evaluation of Deep Learning Models for Identifying Surgical Actions and Measuring Performance

Shuja Khalid, Mitchell Goldenberg, Teodor Grantcharov, Babak Taati, Frank Rudzicz
2020 JAMA Network Open  
To evaluate a framework for assessing surgical video clips by categorizing them based on the surgical step being performed and the level of the surgeon's competence.  ...  The provided architectures achieved accuracy in surgical action and performance calculation tasks using only video input.  ...  Discussion In this study, modeling sequences with neural network embeddings provided state-of-the-art results in surgical action detection using only video input.  ... 
doi:10.1001/jamanetworkopen.2020.1664 pmid:32227178 fatcat:mu64sndx2ffd3fm7tn3eiihvgy

Towards more efficient CNN-based surgical tools classification using transfer learning

Jaafar Jaafari, Samira Douzi, Khadija Douzi, Badr Hssina
2021 Journal of Big Data  
Furthermore, we implement a fine-tuned CNN to tackle the automatic tool detection during a surgery, with prospective use in the teaching field, evaluating surgeons, and surgical quality assessment (SQA  ...  Moreover, deep learning has embroiled in every facet of life due to the availability of large datasets and the emergence of convolutional neural networks (CNN) that have paved the way for the development  ...  Authors'contributions All authors read and approved the final manuscript. Funding  ... 
doi:10.1186/s40537-021-00509-8 fatcat:3ozbhxdtyzdwliskqdj2zyikr4

Endoscopic Image-Based Skill Assessment in Robot-Assisted Minimally Invasive Surgery

Gábor Lajkó, Renáta Nagyné Elek, Tamás Haidegger
2021 Sensors  
This paper introduces a general 2D image-based solution that enables the creation and application of surgical skill assessment in any training environment.  ...  The highest performing method, the Residual Neural Network, reached means of 81.89%, 84.23% and 83.54% accuracy for the skills of Suturing, Needle-Passing and Knot-Tying, respectively.  ...  Based on the results, we can conclude that the Residual Neural Network performs the best in our video data-based surgical skill assessment approach, closely followed by the combined model of CNN and LSTM  ... 
doi:10.3390/s21165412 pmid:34450854 pmcid:PMC8398563 fatcat:p44cweh5gjgz3dbipobcqoq524

Video-based surgical skill assessment using 3D convolutional neural networks [article]

Isabel Funke and Sören Torge Mees and Jürgen Weitz and Stefanie Speidel
2019 arXiv   pre-print
Conclusions: Our results demonstrate the feasibility of deep learning-based assessment of technical skill from surgical video.  ...  In contrast, we investigate a method for automatic, objective skill assessment that requires video data only.  ...  Conflict of Interest: The authors, Isabel Funke, Sören Torge Mees, Jürgen Weitz, and Stefanie Speidel, declare that they have no conflict of interest.  ... 
arXiv:1903.02306v2 fatcat:pp6aipfmkjfltbydyqqqcruleu

The impact of ensemble learning on surgical tools classification during laparoscopic cholecystectomy

Jaafar Jaafari, Samira Douzi, Khadija Douzi, Badr Hssina
2022 Journal of Big Data  
The automatic identification of tool presence in laparoscopic videos leads to detecting what tools are used at each time in surgery and helps in the automatic recognition of surgical workflow.  ...  The aim of this paper is to predict surgical tools from laparoscopic videos using three states of the arts CNNs, namely: VGG19, Inception v-4, and NASNet-A.  ...  Lshirbaji [23] proposed a deep learning-based approach to detect surgical tools in laparoscopic images using a convolutional neural network (VGG16) in combination with two long short-term memory (LSTM  ... 
doi:10.1186/s40537-022-00602-6 fatcat:ygmryzlh6nawrckm23bum3z5gu

A real-time spatiotemporal AI model analyzes skill in open surgical videos [article]

Emmett D. Goodman, Krishna K. Patel, Yilun Zhang, William Locke, Chris J. Kennedy, Rohan Mehrotra, Stephen Ren, Melody Guan, Maren Downing, Hao Wei Chen, Jevin Z. Clark, Gabriel A. Brat (+1 others)
2021 arXiv   pre-print
Using this dataset, we developed a multi-task AI model capable of real-time understanding of surgical behaviors, hands, and tools - the building blocks of procedural flow and surgeon skill.  ...  surgical skill related to efficiency of hand motion.  ...  We thank Daniel Copeland and Michael Zhang for their contributions to dataset curation.  ... 
arXiv:2112.07219v1 fatcat:rprjzwntajgfdbis4ysrzpphha

A Review on Deep Learning in Minimally Invasive Surgery

Irene Rivas-Blanco, Carlos J. Perez-Del-Pulgar, Isabel Garcia-Morales, Victor F. Munoz
2021 IEEE Access  
[15] developed an approach leveraging region-based convolutional neural networks (R-CNN) to perform spatial detection of tools, and then they used this information to analyze the movement of the tools  ...  [30] propose monitoring tool usage during surgery using convolutional and recurrent neural networks.  ...  Her research interests include process automation, control techniques, collaborative robotics, and surgical robotics.  ... 
doi:10.1109/access.2021.3068852 fatcat:gfpghqfptzdktlody5z263cdju

Robust Real-Time Detection of Laparoscopic Instruments in Robot Surgery Using Convolutional Neural Networks with Motion Vector Prediction

Kyungmin Jo, Yuna Choi, Jaesoon Choi, Jong Woo Chung
2019 Applied Sciences  
We propose a new real-time detection algorithm for detection of surgical instruments using convolutional neural networks (CNNs).  ...  This algorithm is based on an object detection system YOLO9000 and ensures continuity of detection of the surgical tools in successive imaging frames based on motion vector prediction.  ...  Detection with YOLO9000 The proposed method detects a surgical tool using YOLO9000, which is based on a convolutional neural network (CNN).  ... 
doi:10.3390/app9142865 fatcat:rbvjrmbnqrgohfpzuwde6c7koe
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