Detection and segmentation method of surgical instruments based on improved YOLOv5s

Xiao-liang MENG; Ji-kang ZHAO; Xiao-yu WANG; Li-ye ZHANG; Zheng SONG

doi:10.37188/CJLCD.2023-0025

Chinese Journal of Liquid Crystals and Displays, Volume. 38, Issue 12, 1698(2023)

Detection and segmentation method of surgical instruments based on improved YOLOv5s

Xiao-liang MENG, Ji-kang ZHAO, Xiao-yu WANG, Li-ye ZHANG^*, and Zheng SONG

Author Affiliations

School of Computer Science and Technology，Shandong University of Technology，Zibo 255000，China

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References(23)

[1] RIVENSON Y, WU Y C, OZCAN A. Deep learning in holography and coherent imaging[J]. Light: Science & Applications, 8, 85(2019).

[2] ZUO C, QIAN J M, FENG S J et al. Deep learning in optical metrology: a review[J]. Light: Science & Applications, 11, 39(2022).

[3] FU Z M, JIN Z Y, ZHANG C G et al. The future of endoscopic navigation: a review of advanced endoscopic vision technology[J]. IEEE Access, 9, 41144-41167(2021).

[4] JIN A, YEUNG S, JOPLING J et al. Tool detection and operative skill assessment in surgical videos using region-based convolutional neural networks[C], 691-699(2018).

[5] MAHMOOD T, CHO S W, PARK K R. DSRD-Net: dual-stream residual dense network for semantic segmentation of instruments in robot-assisted surgery[J]. Expert Systems with Applications, 202, 117420(2022).

[6] LIU Y Y, ZHAO Z J, CHANG F L et al. An anchor-free convolutional neural network for real-time surgical tool detection in robot-assisted surgery[J]. IEEE Access, 8, 78193-78201(2020).

[7] ZHENG T H, TAO Q C. Semantic segmentation algorithm for images of surgical instruments based on fully convolutional networks[J]. Modern Computer, 80-84(2019).

[8] NI Z L, BIAN G B, ZHOU X H et al. RAUNet: residual attention U-Net for semantic segmentation of cataract surgical instruments[C], 139-149(2019).

[9] NI Z L, ZHOU X H, WANG G A et al. SurgiNet: pyramid attention aggregation and class-wise self-distillation for surgical instrument segmentation[J]. Medical Image Analysis, 76, 102310(2022).

[10] XU C J, YI J B, CAO F et al. Colorectal polyp segmentation algorithm using DoubleUNet network[J]. Optics and Precision Engineering, 30, 970-983(2022).

[11] JHA D, RIEGLER M A, JOHANSEN D et al. DoubleU-Net: a deep convolutional neural network for medical image segmentation[C], 558-564(2020).

[12] YANG M K, YU K, ZHANG C et al. DenseASPP for semantic segmentation in street scenes[C], 3684-3692(2018).

[13] PAN J J, LIU W M, GE P et al. Real-time segmentation and tracking of excised corneal contour by deep neural networks for DALK surgical navigation[J]. Computer Methods and Programs in Biomedicine, 197, 105679(2020).

[14] FAN X C, CHEN C M. Lightweight and high-precision object detection algorithm based on YOLO framework[J]. Chinese Journal of Liquid Crystals and Displays, 38, 945-954(2023).

[15] WOO S, PARK J, LEE J Y et al. CBAM: convolutional block attention module[C], 3-19(2018).

[16] OZAWA T, HAYASHI Y, ODA H et al. Synthetic laparoscopic video generation for machine learning-based surgical instrument segmentation from real laparoscopic video and virtual surgical instruments[J]. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 9, 225-232(2021).

[17] ELFWING S, UCHIBE E, DOYA K. Sigmoid-weighted linear units for neural network function approximation in reinforcement learning[J]. Neural Networks, 107, 3-11(2018).

[18] ELHASSAN M A, YANG C H, HUANG C X et al. SPFNet: subspace pyramid fusion network for semantic segmentation[J/OL]. arXiv(2022).

[19] LI C, ZHOU A J, YAO A B. Omni-dimensional dynamic convolution[C](2022).

[20] WANG C Y, BOCHKOVSKIY A, LIAO H Y M. YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors[C], 7464-7475(2023).

[21] WANG C Y, LIAO M H Y, WU Y H et al. CSPNet: a new backbone that can enhance learning capability of CNN[C], 1571-1580(2020).

[22] YU L T, WANG P C, YU X Y et al. A holistically-nested U-Net: surgical instrument segmentation based on convolutional neural network[J]. Journal of Digital Imaging, 33, 341-347(2020).

[23] SUN Y W, PAN B, FU Y L. Lightweight deep neural network for real-time instrument semantic segmentation in robot assisted minimally invasive surgery[J]. IEEE Robotics and Automation Letters, 6, 3870-3877(2021).

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Xiao-liang MENG, Ji-kang ZHAO, Xiao-yu WANG, Li-ye ZHANG, Zheng SONG. Detection and segmentation method of surgical instruments based on improved YOLOv5s[J]. Chinese Journal of Liquid Crystals and Displays, 2023, 38(12): 1698

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Paper Information

Category: Research Articles

Received: Jan. 31, 2023

Accepted: --

Published Online: Mar. 7, 2024

The Author Email: Li-ye ZHANG (zhangliye@sdut.edu.cn)

DOI:10.37188/CJLCD.2023-0025

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