skip to main content
10.1145/2110363.2110400acmconferencesArticle/Chapter ViewAbstractPublication PagesihiConference Proceedingsconference-collections
research-article

Detection of unsafe action from laparoscopic cholecystectomy video

Published: 28 January 2012 Publication History

Abstract

Wellness and healthcare are central to the lives of all people, young or old, healthy or ill, rich or poor. New computing and behavioral research can lead to transformative changes in the cost-effective delivery of quality and personalized healthcare. Also beyond the daily practice of healthcare and wellbeing, basic information technology research can provide the foundations for new directions in the clinical sciences via tools and analyses that identify subtle but important causal signals in the fusing of clinical, behavioral, environmental and genetic data. In this paper we describe a system that analyzes images from the laparoscopic videos. It indicates the possibility of an injury to the cystic artery by automatically detecting the proximity of the surgical instruments with respect to the cystic artery. The system uses machine learning algorithm to classify images and warn surgeons against probable unsafe actions.

References

[1]
U.S. Health Care Costs. kaiseredu.org. {Online} March 2010. http://www.kaiseredu.org/Issue-Modules/US-Health-Care-Costs/Background-Brief.aspx.
[2]
Weiser, M. s.l. Hot Topics: Ubiquitous Computing.: IEEE Computer, 1993.
[3]
Medicine, Institute of. Medical Surge Capacity: Workshop Summary. Washington D.C : The National Academic Press, 2010.
[4]
Cholecyctectomy - Surgical Removal of Gallbladder. facs.org. {Online} http://www.facs.org/public_info/operation/cholesys.pdf.
[5]
Ancona, E., Zaninotto, G., Rossi, M., Costantini, M., Finco, C., Bovolato, M. The safety and feasibility of laparoscopic cholecystectomy.(1992).
[6]
Laparoscopic Surgery. danaise.com. {Online} http://www.danaise.com/laparoscopic_surgery_7-5.htm.
[7]
Ponsky, Jeffrey L. Complications of laparoscopic cholecystectomy. Issue 3, s.l. : The American Journal of Surgery, 1991, Vol. Volume 161, pp. 393--395.
[8]
Sarkar, A. K., Roy, T. S. Anatomy of the cystic artery arising from the gastroduodenal artery and its choledochal branch - a case report. Department of Anatomy, All India Institute of Medical Sciences. s.l. : Journal of Anatomy, 2000.
[9]
Taniguchi, Y., Ido, K., Kimura, K., Yoshida, Y., Ohtani, M., Kawamoto, C., Isoda, N., Suzuki, T., Kumagai, M. Introduction of a "safety zone" for the safety of laparoscopic cholecystectomy. The American journal of gastroenterology, 09/1993, The American journal of gastroenterology.
[10]
Almutairi, A. F., Hussain, Y.A. M. S. Triangle of Safety Technique: A New Approach to Laparoscopic Cholecystectomy. HPB Surgery, 2000, HPB Surgery.
[11]
Bricon-Souf, N., Newman, C. s.l. Context awareness in health care: A review.: International Journal of Medical Informatics, 2007, International Journal of Medical Informatics, Vol. 76.
[12]
Kjeldskov, J., Skov, M. B. Supporting Work Activities in Healthcare by Mobile Electronic Patient Records. s.l. : SpringerLink, 2004. Vol. 3101.
[13]
P. Ordonez, P. Kodeswaran, V. Korolev, W. Li, O. Walavalkar, B. Elgamil, A. Joshi, T. Finin, Y. Yesha, and I. George. A Ubiquitous Context-Aware Environment for Surgical Training. Washington, DC, USA : IEEE Computer Society, 2007. Proceedings of the 2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services (MobiQuitous) (MOBIQUITOUS '07).
[14]
Blum, T., Feuner, H., Navab, N. Modeling and segmentation of surgical workflow from laparoscopic video. Beijing, China : Springer-Verlag, 2010. Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III. pp. 400--407.
[15]
Anand, A., Pathania, B. S., Singh, G. s.l. Conversion in laparoscopic cholecystectomy: an evaluation study.: JK SCIENCE, Oct.-Dec. 2007, JK SCIENCE, Vol. 9, pp. 171--174.
[16]
Eubanks, T. R., Clements, R. H., Pohl, D., Williams, N., Schaad, D. C., Horgan, S., Pellegrini, C. An Objective Scoring System for Laparoscopic Cholecystectomy. 1999, Journal of American College of Surgeons, Vol. vol. 189, pp. 566--574.
[17]
Glaviź, Z., Begi, L., Rozman, R. 8, s.l. A new device for the detection and recognition of blood vessels in laparoscopic surgery. : Surgical Endoscopy, Aug. 2002, Surgical Endoscopy, Vol. 19, pp. 1197--1200.
[18]
Akbari, H., Kosugi, Y., Kihara, K. 7, s.l. A novel method for artery detection in laparoscopic surgery. : Surgical Endoscopy, Jul. 2008, Surgical Endoscopy, Vol. 22, pp. 1672--1677.
[19]
McKenna, S. J., Nait Charif, H., Frank, T. Towards video understanding for laparoscopic surgery: instrument tracking. Dunedin, New Zealand : s.n., 2005. Image and Vision Computing New Zealand Conference.
[20]
Deserno, T. M., Antani, S., Long, R. Exploring access to scientific literature using content-based image retrieval. Aachen University of Technology, U. S. National Library of Medicine, U. S. National Institutes of Health. Bethesda, MD, USA : National Institutes of Health, 2007.
[21]
Tagare, H. D., Jaffe, C. C., Duncan, J. s.l. Medical image databases: A content-based retrieval approach.: JAMIA, 1997, Journal of the American Medical Informatics Association, Vol. 4, pp. 184--198.
[22]
Greenfield, Lazar J., Mulholland, Michael W., Oldham, Keith T., Zelenock, Gerald B., Lillemoe, Kieth D. Essentials of surgery: scientific principles and practice. s.l. : Lippincott Williams & Wilkins, 1997. pp. 297--300. 0397515324.
[23]
A., Zucker Karl. Surgical laparoscopy. s.l. : Lippincott Williams & Wilkins, November 2000. pp. 125--129. 0683306707.
[24]
Chen, W., Shi, T. Q., Xuan, G. Identifying Computer Graphics Using HSV Color Model and Statistical Moments of Characteristic Functions. Beijing : s.n., 2007. IEEE International Conference on Multimedia and Expo. pp. 1123--1126. 1-4244-1016-9.
[25]
Ruurda, J. P., et al. Feasibility of Robot-Assisted Laparoscopic Surgery: An Evaluation of 35 Robot-Assisted Laparoscopic Cholecystectomies. February 2002, Surgical Laparoscopy, Endoscopy & Percutaneous Techniques, Vol. 12, pp. 41--45.

Cited By

View all
  • (2023)DIGITAL IMAGES CLASSIFICATION IN AUTOMATIC LAPAROSCOPIC DIAGNOSTICSWiadomości Lekarskie10.36740/WLek20230210276:2(251-256)Online publication date: 2023
  • (2020)Proposing novel methods for gynecologic surgical action recognition on laparoscopic videosMultimedia Tools and Applications10.1007/s11042-020-09540-yOnline publication date: 13-Aug-2020
  • (2018)Applications of Image Processing in Laparoscopic SurgeriesComputer Vision10.4018/978-1-5225-5204-8.ch063(1518-1544)Online publication date: 2018
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
IHI '12: Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
January 2012
914 pages
ISBN:9781450307819
DOI:10.1145/2110363
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 January 2012

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. image processing
  2. laparoscopic cholecystectomy
  3. machine learning
  4. situation-awareness

Qualifiers

  • Research-article

Conference

IHI '12
Sponsor:
IHI '12: ACM International Health Informatics Symposium
January 28 - 30, 2012
Florida, Miami, USA

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)1
Reflects downloads up to 19 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2023)DIGITAL IMAGES CLASSIFICATION IN AUTOMATIC LAPAROSCOPIC DIAGNOSTICSWiadomości Lekarskie10.36740/WLek20230210276:2(251-256)Online publication date: 2023
  • (2020)Proposing novel methods for gynecologic surgical action recognition on laparoscopic videosMultimedia Tools and Applications10.1007/s11042-020-09540-yOnline publication date: 13-Aug-2020
  • (2018)Applications of Image Processing in Laparoscopic SurgeriesComputer Vision10.4018/978-1-5225-5204-8.ch063(1518-1544)Online publication date: 2018
  • (2018)Content-based processing and analysis of endoscopic images and videosMultimedia Tools and Applications10.1007/s11042-016-4219-z77:1(1323-1362)Online publication date: 1-Jan-2018
  • (2017)Applications of Image Processing in Laparoscopic SurgeriesHandbook of Research on Data Science for Effective Healthcare Practice and Administration10.4018/978-1-5225-2515-8.ch014(317-343)Online publication date: 2017
  • (2017)Video content analysis of surgical proceduresSurgical Endoscopy10.1007/s00464-017-5878-132:2(553-568)Online publication date: 26-Oct-2017

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media