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
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 .