Automated surgical OSATS prediction from videos

Yachna Sharma; Thomas Plötz; Nils Hammerld; Sebastian Mellor; Roisin McNaney; Patrick Olivier; Sandeep Deshmukh; Andrew McCaskie; Irfan Essa

doi:10.1109/ISBI.2014.6867908

Automated surgical OSATS prediction from videos

Yachna Sharma, Thomas Plötz, Nils Hammerld, Sebastian Mellor, Roisin McNaney, Patrick Olivier, Sandeep Deshmukh, Andrew McCaskie, Irfan Essa

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

27 Citations (Scopus)

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 <0.01) between the ground-truth (given by domain experts) and the OSATS scores predicted by our framework.

Original language	English
Title of host publication	2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)
Subtitle of host publication	Beijing, China 29 April – 2 May 2014
Editors	Laure Blanc-Féraud, Jie Tian
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	461-464
Number of pages	4
ISBN (Electronic)	9781467319614, 9781467319591
ISBN (Print)	9781467319607
DOIs	https://doi.org/10.1109/ISBI.2014.6867908
Publication status	Published - 2014
Externally published	Yes
Event	IEEE International Symposium on Biomedical Imaging (ISBI) 2014 - Beijing, China Duration: 29 Apr 2014 → 2 May 2014 Conference number: 11th https://archives.embs.org/wp-content/archives/ISBI/2014/ https://ieeexplore.ieee.org/xpl/conhome/6861559/proceeding (Proceedings)

Conference

Conference	IEEE International Symposium on Biomedical Imaging (ISBI) 2014
Abbreviated title	ISBI 2014
Country/Territory	China
City	Beijing
Period	29/04/14 → 2/05/14
Internet address	https://archives.embs.org/wp-content/archives/ISBI/2014/ https://ieeexplore.ieee.org/xpl/conhome/6861559/proceeding (Proceedings)

Keywords

Motion texture
OSATS
Surgical skill
Video analysis

Access to Document

10.1109/ISBI.2014.6867908

Cite this

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 L. Blanc-Féraud, & J. Tian (Eds.), 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014): Beijing, China 29 April – 2 May 2014 (pp. 461-464). Article 6867908 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISBI.2014.6867908

@inproceedings{e46fef93b09a4a11a6c87087c3873574,

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 <0.01) between the ground-truth (given by domain experts) and the OSATS scores predicted by our framework.",

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",

doi = "10.1109/ISBI.2014.6867908",

language = "English",

isbn = "9781467319607",

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booktitle = "2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE International Symposium on Biomedical Imaging (ISBI) 2014, ISBI 2014 ; Conference date: 29-04-2014 Through 02-05-2014",

url = "https://archives.embs.org/wp-content/archives/ISBI/2014/, https://ieeexplore.ieee.org/xpl/conhome/6861559/proceeding",

}

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 L Blanc-Féraud & J Tian (eds), 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014): Beijing, China 29 April – 2 May 2014., 6867908, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 461-464, IEEE International Symposium on Biomedical Imaging (ISBI) 2014, Beijing, China, 29/04/14. https://doi.org/10.1109/ISBI.2014.6867908

Automated surgical OSATS prediction from videos. / Sharma, Yachna; Plötz, Thomas; Hammerld, Nils et al.
2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014): Beijing, China 29 April – 2 May 2014. ed. / Laure Blanc-Féraud; Jie Tian. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 461-464 6867908.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

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

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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 <0.01) between the ground-truth (given by domain experts) and the OSATS scores predicted by our framework.

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 <0.01) between the ground-truth (given by domain experts) and the OSATS scores predicted by our framework.

KW - Motion texture

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M3 - Conference Paper

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SN - 9781467319607

SP - 461

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BT - 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

A2 - Blanc-Féraud, Laure

A2 - Tian, Jie

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - IEEE International Symposium on Biomedical Imaging (ISBI) 2014

Y2 - 29 April 2014 through 2 May 2014

ER -

Sharma Y, Plötz T, Hammerld N, Mellor S, McNaney R, Olivier P et al. Automated surgical OSATS prediction from videos. In Blanc-Féraud L, Tian J, editors, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014): Beijing, China 29 April – 2 May 2014. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2014. p. 461-464. 6867908 doi: 10.1109/ISBI.2014.6867908

Automated surgical OSATS prediction from videos

Abstract

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Keywords

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