21.6.1 Surgical Instruments, Detection, Tracking

Chapter Contents (Back)
Surgery. Surgical Instruments.

Edinburgh Simulated Surgical Tools Dataset (RGBD),
2023
WWW Link. Dataset, Surgery.
See also University of Edinburgh. contains synthetic (25K) and real (14K) RGBD images of five simulated surgical tools. Some images contain isolated tools, others contain multiple tools.

West, J.B., Maurer, Jr., C.R.,
Designing optically tracked instruments for image-guided surgery,
MedImg(23), No. 5, May 2004, pp. 533-545.
IEEE Abstract. 0406
BibRef

Stoll, J., Ren, H., Dupont, P.E.,
Passive Markers for Tracking Surgical Instruments in Real-Time 3-D Ultrasound Imaging,
MedImg(31), No. 3, March 2012, pp. 563-575.
IEEE DOI 1203
BibRef

Bouget, D., Benenson, R., Omran, M., Riffaud, L., Schiele, B., Jannin, P.,
Detecting Surgical Tools by Modelling Local Appearance and Global Shape,
MedImg(34), No. 12, December 2015, pp. 2603-2617.
IEEE DOI 1601
computer vision BibRef

Estrada, S., Duran, C., Schulz, D., Bismuth, J., Byrne, M.D., O'Malley, M.K.,
Smoothness of Surgical Tool Tip Motion Correlates to Skill in Endovascular Tasks,
HMS(46), No. 5, October 2016, pp. 647-659.
IEEE DOI 1610
biomedical education BibRef

Sbernini, L., Quitadamo, L.R., Riillo, F., Lorenzo, N.D., Gaspari, A.L., Saggio, G.,
Sensory-Glove-Based Open Surgery Skill Evaluation,
HMS(48), No. 2, April 2018, pp. 213-218.
IEEE DOI 1804
Instruments, Manuals, Sensors, Support vector machines, Surgery, Task analysis, Tracking, Gesture recognition, manual dexterity, wearable systems BibRef

Du, X., Kurmann, T., Chang, P.L., Allan, M., Ourselin, S., Sznitman, R., Kelly, J.D., Stoyanov, D.,
Articulated Multi-Instrument 2-D Pose Estimation Using Fully Convolutional Networks,
MedImg(37), No. 5, May 2018, pp. 1276-1287.
IEEE DOI 1805
Instruments, Joints, Pose estimation, Robot kinematics, Semantics, Surgery, Surgical instrument detection, surgical vision BibRef

Allan, M., Ourselin, S., Hawkes, D.J., Kelly, J.D., Stoyanov, D.,
3-D Pose Estimation of Articulated Instruments in Robotic Minimally Invasive Surgery,
MedImg(37), No. 5, May 2018, pp. 1204-1213.
IEEE DOI 1805
Cameras, Instruments, Robots, Solid modeling, Surgery, Transforms, robotic surgery BibRef

He, W.H.[Wen-Hao], Song, H.T.[Hai-Tao], Guo, Y.[Yue], Bian, G.B.[Gui-Bin], Sun, Y.J.[Yue-Jie], Zhou, X.W.[Xiao-Wei], Wang, X.N.[Xiao-Nan],
Multiscale matters for part segmentation of instruments in robotic surgery,
IET-IPR(14), No. 13, November 2020, pp. 3215-3222.
DOI Link 2012
BibRef

Garcia-Peraza-Herrera, L.C.[Luis C.], Fidon, L.[Lucas], d'Ettorre, C.[Claudia], Stoyanov, D.[Danail], Vercauteren, T.[Tom], Ourselin, S.[Sébastien],
Image Compositing for Segmentation of Surgical Tools Without Manual Annotations,
MedImg(40), No. 5, May 2021, pp. 1450-1460.
IEEE DOI 2105
Image segmentation, Instruments, Tools, Training, Task analysis, Surgery, Manuals, Image compositing, chroma key, tool segmentation BibRef

Wang, X.Y.[Xiao-Yan], Wang, L.[Luyao], Zhong, X.Y.[Xing-Yu], Bai, C.[Cong], Huang, X.J.[Xiao-Jie], Zhao, R.Y.[Rui-Yi], Xia, M.[Ming],
PaI-Net: A modified U-Net of reducing semantic gap for surgical instrument segmentation,
IET-IPR(15), No. 12, 2021, pp. 2959-2969.
DOI Link 2109
BibRef

Liu, J.[Jie], Guo, X.Q.[Xiao-Qing], Yuan, Y.X.[Yi-Xuan],
Graph-Based Surgical Instrument Adaptive Segmentation via Domain-Common Knowledge,
MedImg(41), No. 3, March 2022, pp. 715-726.
IEEE DOI 2203
Surgery, Instruments, Image segmentation, Prototypes, Feature extraction, Task analysis, Semantics, domain-common knowledge BibRef

Kwok, K.W.[Ka-Wai], Wurdemann, H.[Helge], Arezzo, A.[Alberto], Menciassi, A.[Arianna], Althoefer, K.[Kaspar],
Soft Robot-Assisted Minimally Invasive Surgery and Interventions: Advances and Outlook,
PIEEE(110), No. 7, July 2022, pp. 871-892.
IEEE DOI 2206
Medical robotics, Robot sensing systems, Soft robotics, Sensors, Minimally invasive surgery, Endoscopes, Instruments, tunable stiffness BibRef

Psychogyios, D.[Dimitrios], Mazomenos, E.[Evangelos], Vasconcelos, F.[Francisco], Stoyanov, D.[Danail],
MSDESIS: Multitask Stereo Disparity Estimation and Surgical Instrument Segmentation,
MedImg(41), No. 11, November 2022, pp. 3218-3230.
IEEE DOI 2211
Task analysis, Multitasking, Estimation, Feature extraction, Surgery, Head, Computer assisted interventions, computational stereo, instrument segmentation BibRef

Colleoni, E.[Emanuele], Psychogyios, D.[Dimitris], van Amsterdam, B.[Beatrice], Vasconcelos, F.[Francisco], Stoyanov, D.[Danail],
SSIS-Seg: Simulation-Supervised Image Synthesis for Surgical Instrument Segmentation,
MedImg(41), No. 11, November 2022, pp. 3074-3086.
IEEE DOI 2211
Image segmentation, Instruments, Data models, Training, Generators, Image synthesis, Surgery, Image-to-image translation, surgical vision BibRef

Rodrigues, M.[Mark], Mayo, M.[Michael], Patros, P.[Panos],
Surgical Tool Datasets for Machine Learning Research: A Survey,
IJCV(130), No. 9, September 2022, pp. 2222-2248.
Springer DOI 2208
BibRef

Yin, B.[Bohan], Wang, S.S.[Sheng-Sheng], Lu, S.[Shuzhen], Wang, G.Y.[Guang-Yao], Dong, L.Y.[Li-Yan],
Error analysis driven network modification for surgical tools detection in laparoscopic frames,
IJIST(33), No. 1, 2023, pp. 192-203.
DOI Link 2301
deep learning, error analysis, laparoscopic surgery, tool detection BibRef

Lou, A.[Ange], Tawfik, K.[Kareem], Yao, X.[Xing], Liu, Z.T.[Zi-Teng], Noble, J.[Jack],
Min-Max Similarity: A Contrastive Semi-Supervised Deep Learning Network for Surgical Tools Segmentation,
MedImg(42), No. 10, October 2023, pp. 2832-2841.
IEEE DOI 2310
BibRef

Shen, W.T.[Wen-Ting], Wang, Y.[Yaonan], Liu, M.[Min], Wang, J.Z.[Jia-Zheng], Ding, R.J.[Ren-Jie], Zhang, Z.[Zhe], Meijering, E.[Erik],
Branch Aggregation Attention Network for Robotic Surgical Instrument Segmentation,
MedImg(42), No. 11, November 2023, pp. 3408-3419.
IEEE DOI Code:
WWW Link. 2311
BibRef

Tao, R.[Rong], Zou, X.Y.[Xiao-Yang], Zheng, G.[Guoyan],
LAST: LAtent Space-Constrained Transformers for Automatic Surgical Phase Recognition and Tool Presence Detection,
MedImg(42), No. 11, November 2023, pp. 3256-3268.
IEEE DOI 2311
BibRef

Ishiyama, R.[Rui], Frřiland, P.H.L.[Per Helge Litzheim], Řvrebotn, S.A.[Stein-Asle],
Automated Identification of Surgical Instruments without Tagging: Implementation in Real Hospital Work Environment,
MVA23(1-4)
DOI Link 2403
Costs, Automation, Hospitals, Instruments, Surgery, Documentation, Tagging BibRef


Baby, B.[Britty], Thapar, D.[Daksh], Chasmai, M.[Mustafa], Banerjee, T.[Tamajit], Dargan, K.[Kunal], Suri, A.[Ashish], Banerjee, S.[Subhashis], Arora, C.[Chetan],
From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments,
WACV23(6180-6190)
IEEE DOI 2302
Training, Image segmentation, Technological innovation, Instruments, Source coding, Neural networks, Imaging BibRef

Philipp, M.[Markus], Alperovich, A.[Anna], Gutt-Will, M.[Marielena], Mathis, A.[Andrea], Saur, S.[Stefan], Raabe, A.[Andreas], Mathis-Ullrich, F.[Franziska],
Dynamic CNNs using uncertainty to overcome domain generalization for surgical instrument localization,
WACV22(1727-1736)
IEEE DOI 2202
Location awareness, Uncertainty, Minimally invasive surgery, Instruments, Soft sensors, Vision Systems and Applications BibRef

Leifman, G.[George], Aides, A.[Amit], Golany, T.[Tomer], Freedman, D.[Daniel], Rivlin, E.[Ehud],
Pixel-accurate Segmentation of Surgical Tools based on Bounding Box Annotations,
ICPR22(5096-5103)
IEEE DOI 2212
Training, Laparoscopes, Image segmentation, Minimally invasive surgery, Instruments BibRef

Liu, D.C.[Dao-Chang], Li, Q.Y.[Qi-Yue], Jiang, T.T.[Ting-Ting], Wang, Y.Z.[Yi-Zhou], Miao, R.L.[Ru-Lin], Shan, F.[Fei], Li, Z.[Ziyu],
Towards Unified Surgical Skill Assessment,
CVPR21(9517-9526)
IEEE DOI 2111
Minimally invasive surgery, Correlation, Surgery, Manuals, Tools, Safety BibRef

Benjumea, E.[Eberto], Sierra, J.S.[Juan S.], Meza, J.[Jhacson], Marrugo, A.G.[Andres G.],
Multi-target Attachment for Surgical Instrument Tracking,
MCPR21(345-354).
Springer DOI 2108
BibRef

Kayhan, M.[Mert], Köpüklü, O.[Okan], Sarhan, M.H.[Mhd Hasan], Yigitsoy, M.[Mehmet], Eslami, A.[Abouzar], Rigoll, G.[Gerhard],
Deep Attention Based Semi-supervised 2d-pose Estimation for Surgical Instruments,
AIHA20(444-460).
Springer DOI 2103
BibRef

Jin, A., Yeung, S., Jopling, J., Krause, J., Azagury, D., Milstein, A., Fei-Fei, L.,
Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks,
WACV18(691-699)
IEEE DOI 1806
biomedical equipment, biomedical optical imaging, image motion analysis, medical image processing, neural nets, Videos BibRef

Kügler, D.[David], Jastrzebski, M.A.[Martin Andrade], Mukhopadhyay, A.[Anirban],
Instrument Pose Estimation Using Registration for Otobasis Surgery,
WBIR18(105-114).
Springer DOI 1806
BibRef

Wesierski, D.[Daniel], Cygert, S.[Sebastian],
Shape-Based Pose Estimation of Robotic Surgical Instruments,
CARE17(3-15).
Springer DOI 1711
BibRef

García-Peraza-Herrera, L.C.[Luis C.], Li, W.Q.[Wen-Qi], Gruijthuijsen, C.[Caspar], Devreker, A.[Alain], Attilakos, G.[George], Deprest, J.[Jan], Vander Poorten, E.[Emmanuel], Stoyanov, D.[Danail], Vercauteren, T.[Tom], Ourselin, S.[Sébastien],
Real-Time Segmentation of Non-rigid Surgical Tools Based on Deep Learning and Tracking,
CARE16(84-95).
Springer DOI 1703
BibRef

Reiter, A.[Austin], Allen, P.K.[Peter K.], Zhao, T.[Tao],
Learning features on robotic surgical tools,
MCV12(38-43).
IEEE DOI 1207
BibRef

Navarro, A.[Agustin], Villarraga, E.[Edgar], Aranda, J.[Joan],
Relative Pose Estimation of Surgical Tools in Assisted Minimally Invasive Surgery,
IbPRIA07(II: 428-435).
Springer DOI 0706
BibRef

MacLachlan, R., and Riviere, C.,
Optical Tracking for Performance Testing of Microsurgical Instruments,
CMU-RI-TR-07-01, January, 2007.
WWW Link. BibRef 0701

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Laparoscopy, Surgery .


Last update:May 23, 2024 at 14:31:23