Automatic video tagging method for cortical mapping in awake craniotomy records

Toshihiko Nishimura, Tomoharu Nagao, Hiroshi Iseki, Yoshihiro Muragaki, Manabu Tamura, Shinji Minami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Operation video recording is one of efficient methods for analyzing surgical workflow and intraoperative incident detection. In "Intelligent Operating Room" at Tokyo Women's Medical University Hospital, the special neurological surgery called awake craniotomy is recorded by video recording system IEMAS (Intraoperative Examination Monitor for Awake Surgery). There are a number of useful video records of surgical procedure such as patient reactions and surgical operations. However, these surgical event tags which are used for surgcial workflow analysis are not contained in IEMAS records. IEMAS is composed multi-view video cameras, so manual tagging for video records is a lot of labor because of the large length of surgical operation videos. In awake craniotomy, electrical stimulation is one of significant surgical operations for detecting eloquent brain areas. In this paper, we propose the automatic detection method for the stimulation points onto patient's brain areas from raw IEMAS video records by using image processing approach. In the previous work, we proposed stimulation timing detection method from surgery sound records of IEMAS. Hence, we propose a detection method of surgical instrument for electrical stimulation in order to tag the stimulated positions on surgical view. However, detected positions on the video frame coordinates depend on camera view changes. Therefore, we map video frame positions to representative video frame positions by using homography transformation in order to enable to analyze stimulated points relation. We applied automatic video tagging method for several raw IEMAS video records and show its performance.

Original languageEnglish
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2637-2642
Number of pages6
Volume2014-January
EditionJanuary
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014 - San Diego, United States
Duration: 2014 Oct 52014 Oct 8

Other

Other2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014
CountryUnited States
CitySan Diego
Period14/10/514/10/8

Fingerprint

Surgery
Video recording
Brain
Operating rooms
Video cameras
Image processing
Cameras
Acoustic waves
Personnel

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

Cite this

Nishimura, T., Nagao, T., Iseki, H., Muragaki, Y., Tamura, M., & Minami, S. (2014). Automatic video tagging method for cortical mapping in awake craniotomy records. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (January ed., Vol. 2014-January, pp. 2637-2642). [6974325] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/smc.2014.6974325

Automatic video tagging method for cortical mapping in awake craniotomy records. / Nishimura, Toshihiko; Nagao, Tomoharu; Iseki, Hiroshi; Muragaki, Yoshihiro; Tamura, Manabu; Minami, Shinji.

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. Vol. 2014-January January. ed. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2637-2642 6974325.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nishimura, T, Nagao, T, Iseki, H, Muragaki, Y, Tamura, M & Minami, S 2014, Automatic video tagging method for cortical mapping in awake craniotomy records. in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. January edn, vol. 2014-January, 6974325, Institute of Electrical and Electronics Engineers Inc., pp. 2637-2642, 2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014, San Diego, United States, 14/10/5. https://doi.org/10.1109/smc.2014.6974325
Nishimura T, Nagao T, Iseki H, Muragaki Y, Tamura M, Minami S. Automatic video tagging method for cortical mapping in awake craniotomy records. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. January ed. Vol. 2014-January. Institute of Electrical and Electronics Engineers Inc. 2014. p. 2637-2642. 6974325 https://doi.org/10.1109/smc.2014.6974325
Nishimura, Toshihiko ; Nagao, Tomoharu ; Iseki, Hiroshi ; Muragaki, Yoshihiro ; Tamura, Manabu ; Minami, Shinji. / Automatic video tagging method for cortical mapping in awake craniotomy records. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. Vol. 2014-January January. ed. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 2637-2642
@inproceedings{98e4d1bee79441e28f130ed098ff04a0,
title = "Automatic video tagging method for cortical mapping in awake craniotomy records",
abstract = "Operation video recording is one of efficient methods for analyzing surgical workflow and intraoperative incident detection. In {"}Intelligent Operating Room{"} at Tokyo Women's Medical University Hospital, the special neurological surgery called awake craniotomy is recorded by video recording system IEMAS (Intraoperative Examination Monitor for Awake Surgery). There are a number of useful video records of surgical procedure such as patient reactions and surgical operations. However, these surgical event tags which are used for surgcial workflow analysis are not contained in IEMAS records. IEMAS is composed multi-view video cameras, so manual tagging for video records is a lot of labor because of the large length of surgical operation videos. In awake craniotomy, electrical stimulation is one of significant surgical operations for detecting eloquent brain areas. In this paper, we propose the automatic detection method for the stimulation points onto patient's brain areas from raw IEMAS video records by using image processing approach. In the previous work, we proposed stimulation timing detection method from surgery sound records of IEMAS. Hence, we propose a detection method of surgical instrument for electrical stimulation in order to tag the stimulated positions on surgical view. However, detected positions on the video frame coordinates depend on camera view changes. Therefore, we map video frame positions to representative video frame positions by using homography transformation in order to enable to analyze stimulated points relation. We applied automatic video tagging method for several raw IEMAS video records and show its performance.",
author = "Toshihiko Nishimura and Tomoharu Nagao and Hiroshi Iseki and Yoshihiro Muragaki and Manabu Tamura and Shinji Minami",
year = "2014",
doi = "10.1109/smc.2014.6974325",
language = "English",
volume = "2014-January",
pages = "2637--2642",
booktitle = "Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
edition = "January",

}

TY - GEN

T1 - Automatic video tagging method for cortical mapping in awake craniotomy records

AU - Nishimura, Toshihiko

AU - Nagao, Tomoharu

AU - Iseki, Hiroshi

AU - Muragaki, Yoshihiro

AU - Tamura, Manabu

AU - Minami, Shinji

PY - 2014

Y1 - 2014

N2 - Operation video recording is one of efficient methods for analyzing surgical workflow and intraoperative incident detection. In "Intelligent Operating Room" at Tokyo Women's Medical University Hospital, the special neurological surgery called awake craniotomy is recorded by video recording system IEMAS (Intraoperative Examination Monitor for Awake Surgery). There are a number of useful video records of surgical procedure such as patient reactions and surgical operations. However, these surgical event tags which are used for surgcial workflow analysis are not contained in IEMAS records. IEMAS is composed multi-view video cameras, so manual tagging for video records is a lot of labor because of the large length of surgical operation videos. In awake craniotomy, electrical stimulation is one of significant surgical operations for detecting eloquent brain areas. In this paper, we propose the automatic detection method for the stimulation points onto patient's brain areas from raw IEMAS video records by using image processing approach. In the previous work, we proposed stimulation timing detection method from surgery sound records of IEMAS. Hence, we propose a detection method of surgical instrument for electrical stimulation in order to tag the stimulated positions on surgical view. However, detected positions on the video frame coordinates depend on camera view changes. Therefore, we map video frame positions to representative video frame positions by using homography transformation in order to enable to analyze stimulated points relation. We applied automatic video tagging method for several raw IEMAS video records and show its performance.

AB - Operation video recording is one of efficient methods for analyzing surgical workflow and intraoperative incident detection. In "Intelligent Operating Room" at Tokyo Women's Medical University Hospital, the special neurological surgery called awake craniotomy is recorded by video recording system IEMAS (Intraoperative Examination Monitor for Awake Surgery). There are a number of useful video records of surgical procedure such as patient reactions and surgical operations. However, these surgical event tags which are used for surgcial workflow analysis are not contained in IEMAS records. IEMAS is composed multi-view video cameras, so manual tagging for video records is a lot of labor because of the large length of surgical operation videos. In awake craniotomy, electrical stimulation is one of significant surgical operations for detecting eloquent brain areas. In this paper, we propose the automatic detection method for the stimulation points onto patient's brain areas from raw IEMAS video records by using image processing approach. In the previous work, we proposed stimulation timing detection method from surgery sound records of IEMAS. Hence, we propose a detection method of surgical instrument for electrical stimulation in order to tag the stimulated positions on surgical view. However, detected positions on the video frame coordinates depend on camera view changes. Therefore, we map video frame positions to representative video frame positions by using homography transformation in order to enable to analyze stimulated points relation. We applied automatic video tagging method for several raw IEMAS video records and show its performance.

UR - http://www.scopus.com/inward/record.url?scp=84938078159&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84938078159&partnerID=8YFLogxK

U2 - 10.1109/smc.2014.6974325

DO - 10.1109/smc.2014.6974325

M3 - Conference contribution

VL - 2014-January

SP - 2637

EP - 2642

BT - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

PB - Institute of Electrical and Electronics Engineers Inc.

ER -