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Automated surgical OSATS prediction from videos. / Sharma, Yachna; Plötz, Thomas; Hammerld, Nils et al.
2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 461-464 6867908.
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Sharma, Y, Plötz, T, Hammerld, N, Mellor, S
, McNaney, R, Olivier, P, Deshmukh, S, McCaskie, A & Essa, I 2014,
Automated surgical OSATS prediction from videos. in
2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014., 6867908, Institute of Electrical and Electronics Engineers Inc., pp. 461-464, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Beijing, China,
29/04/14.
https://doi.org/10.1109/ISBI.2014.6867908APA
Sharma, Y., Plötz, T., Hammerld, N., Mellor, S.
, McNaney, R., Olivier, P., Deshmukh, S., McCaskie, A., & Essa, I. (2014).
Automated surgical OSATS prediction from videos. In
2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 (pp. 461-464). Article 6867908 Institute of Electrical and Electronics Engineers Inc..
https://doi.org/10.1109/ISBI.2014.6867908Vancouver
Sharma Y, Plötz T, Hammerld N, Mellor S
, McNaney R, Olivier P et al.
Automated surgical OSATS prediction from videos. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 461-464. 6867908 doi: 10.1109/ISBI.2014.6867908
Author
Sharma, Yachna ; Plötz, Thomas ; Hammerld, Nils et al. /
Automated surgical OSATS prediction from videos. 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 461-464
Bibtex
@inproceedings{7d04254e11f94422a5e217e42dfe278a,
title = "Automated surgical OSATS prediction from videos",
abstract = "The assessment of surgical skills is an essential part of medical training. The prevalent manual evaluations by expert surgeons are time consuming and often their outcomes vary substantially from one observer to another. We present a video-based framework for automated evaluation of surgical skills based on the Objective Structured Assessment of Technical Skills (OSATS) criteria. We encode the motion dynamics via frame kernel matrices, and represent the motion granularity by texture features. Linear discriminant analysis is used to derive a reduced dimensionality feature space followed by linear regression to predict OSATS skill scores. We achieve statistically significant correlation (p-value ",
keywords = "Motion texture, OSATS, Surgical skill, Video analysis",
author = "Yachna Sharma and Thomas Pl{\"o}tz and Nils Hammerld and Sebastian Mellor and Roisin McNaney and Patrick Olivier and Sandeep Deshmukh and Andrew McCaskie and Irfan Essa",
year = "2014",
month = jul,
day = "29",
doi = "10.1109/ISBI.2014.6867908",
language = "English",
isbn = "9781467319591",
pages = "461--464",
booktitle = "2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",
note = "2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 ; Conference date: 29-04-2014 Through 02-05-2014",
}
RIS
TY - GEN
T1 - Automated surgical OSATS prediction from videos
AU - Sharma, Yachna
AU - Plötz, Thomas
AU - Hammerld, Nils
AU - Mellor, Sebastian
AU - McNaney, Roisin
AU - Olivier, Patrick
AU - Deshmukh, Sandeep
AU - McCaskie, Andrew
AU - Essa, Irfan
PY - 2014/7/29
Y1 - 2014/7/29
N2 - The assessment of surgical skills is an essential part of medical training. The prevalent manual evaluations by expert surgeons are time consuming and often their outcomes vary substantially from one observer to another. We present a video-based framework for automated evaluation of surgical skills based on the Objective Structured Assessment of Technical Skills (OSATS) criteria. We encode the motion dynamics via frame kernel matrices, and represent the motion granularity by texture features. Linear discriminant analysis is used to derive a reduced dimensionality feature space followed by linear regression to predict OSATS skill scores. We achieve statistically significant correlation (p-value
AB - The assessment of surgical skills is an essential part of medical training. The prevalent manual evaluations by expert surgeons are time consuming and often their outcomes vary substantially from one observer to another. We present a video-based framework for automated evaluation of surgical skills based on the Objective Structured Assessment of Technical Skills (OSATS) criteria. We encode the motion dynamics via frame kernel matrices, and represent the motion granularity by texture features. Linear discriminant analysis is used to derive a reduced dimensionality feature space followed by linear regression to predict OSATS skill scores. We achieve statistically significant correlation (p-value
KW - Motion texture
KW - OSATS
KW - Surgical skill
KW - Video analysis
U2 - 10.1109/ISBI.2014.6867908
DO - 10.1109/ISBI.2014.6867908
M3 - Conference contribution/Paper
AN - SCOPUS:84927943659
SN - 9781467319591
SP - 461
EP - 464
BT - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Y2 - 29 April 2014 through 2 May 2014
ER -
