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Informatics Approach to Improving Su...

Islam, Gazi.

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Informatics Approach to Improving Surgical Skills Training.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Informatics Approach to Improving Surgical Skills Training./
Author:	Islam, Gazi.
Description:	138 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-02(E), Section: B.
Contained By:	Dissertation Abstracts International75-02B(E).
Subject:	Biology, Bioinformatics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3600300
ISBN:	9781303503771

Informatics Approach to Improving Surgical Skills Training.
Islam, Gazi.

Informatics Approach to Improving Surgical Skills Training. - 138 p.

Source: Dissertation Abstracts International, Volume: 75-02(E), Section: B.

Thesis (Ph.D.)--Arizona State University, 2013.

Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.

ISBN: 9781303503771Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Informatics Approach to Improving Surgical Skills Training.
LDR:02951nam a2200313 4500 001 1964651
005 20141010092630.5
008 150210s2013 ||||||||||||||||| ||eng d
020 $a 9781303503771
035 $a (MiAaPQ)AAI3600300
035 $a AAI3600300
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100 1 $a Islam, Gazi. $3 2101140
245 1 0 $a Informatics Approach to Improving Surgical Skills Training.
300 $a 138 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-02(E), Section: B.
500 $a Advisers: Baoxin Li; Jianming Liang.
502 $a Thesis (Ph.D.)--Arizona State University, 2013.
520 $a Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
590 $a School code: 0010.
650 4 $a Biology, Bioinformatics. $3 1018415
650 4 $a Computer Science. $3 626642
650 4 $a Education, Health. $3 1017668
650 4 $a Education, Technology of. $3 1018012
650 4 $a Health Sciences, Surgery. $3 1681670
690 $a 0715
690 $a 0984
690 $a 0680
690 $a 0710
690 $a 0576
710 2 $a Arizona State University. $b Biomedical Informatics. $3 1680799
773 0 $t Dissertation Abstracts International $g 75-02B(E).
790 $a 0010
791 $a Ph.D.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3600300