Development of Computer Vision Algorithm for Surgical Skill Assessment

Islam, Gazi; Kahol, Kanav; Ferrara, John J.; Gray, Richard

doi:10.1007/978-3-642-23902-1_6

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…Traditional medical skill evaluation methods usually need contact sensors which will affect the operation of doctors. To overcome this disadvantage, [43], [44] proposed a surgical skill method based on visual information. Based on Islam et al [43], [44] improved the algorithm to realtime, added feedback function and tested the model in the real surgical video.…”

Section: B Aqa Models In Medical Carementioning

confidence: 99%

“…To overcome this disadvantage, [43], [44] proposed a surgical skill method based on visual information. Based on Islam et al [43], [44] improved the algorithm to realtime, added feedback function and tested the model in the real surgical video. In order to deal with the semantic gap between low-level visual features and high-level surgical skills, Chen et al [45] fused multi-modal information and completed meaningful surgical skill analysis by looking for hidden space.…”

Section: B Aqa Models In Medical Carementioning

confidence: 99%

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A Survey of Video-based Action Quality Assessment

Wang,

Yang,

Zhai

et al. 2022

Preprint

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Human action recognition and analysis have great demand and important application significance in video surveillance, video retrieval, and human-computer interaction. The task of human action quality evaluation requires the intelligent system to automatically and objectively evaluate the action completed by the human. The action quality assessment model can reduce the human and material resources spent in action evaluation and reduce subjectivity. In this paper, we provide a comprehensive survey of existing papers on video-based action quality assessment. Different from human action recognition, the application scenario of action quality assessment is relatively narrow. Most of the existing work focuses on sports and medical care. We first introduce the definition and challenges of human action quality assessment. Then we present the existing datasets and evaluation metrics. In addition, we summarized the methods of sports and medical care according to the model categories and publishing institutions according to the characteristics of the two fields. At the end, combined with recent work, the promising development direction in action quality assessment is discussed.

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Section: B Aqa Models In Medical Carementioning

confidence: 99%

Section: B Aqa Models In Medical Carementioning

confidence: 99%

A Survey of Video-based Action Quality Assessment

Wang,

Yang,

Zhai

et al. 2022

Preprint

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“…Total duration, path length, and number of movements were found to be important for distinguishing between attendings and medical students ( 37 ). Further, computer vision has also been used to extract image-based metrics as a means to quantify surgical skill ( 31 , 32 , 34 , 35 ). Frischknecht et al ( 31 ) analyzed photographs taken post-procedure to assess suturing performance.…”

Section: Introductionmentioning

confidence: 99%

“…Many metrics for skill assessment have been presented in the literature. These metrics can be classified as force-based metrics (15)(16)(17)(18)(19)(20)(21)(22)(23), motion-based metrics (8,18,(23)(24)(25)(26)(27)(28)(29)(30) and imagebased metrics (29,(31)(32)(33)(34)(35)(36)(37)(38)(39). Force-based metrics, such as absolute, mean, and peak forces and force volume (16)(17)(18)23), have been most successful at distinguishing novice vs. expert performance at surgical tasks.…”

mentioning

confidence: 99%

Assessment of open surgery suturing skill: Simulator platform, force-based, and motion-based metrics

et al. 2022

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ObjectiveThis paper focuses on simulator-based assessment of open surgery suturing skill. We introduce a new surgical simulator designed to collect synchronized force, motion, video and touch data during a radial suturing task adapted from the Fundamentals of Vascular Surgery (FVS) skill assessment. The synchronized data is analyzed to extract objective metrics for suturing skill assessment.MethodsThe simulator has a camera positioned underneath the suturing membrane, enabling visual tracking of the needle during suturing. Needle tracking data enables extraction of meaningful metrics related to both the process and the product of the suturing task. To better simulate surgical conditions, the height of the system and the depth of the membrane are both adjustable. Metrics for assessment of suturing skill based on force/torque, motion, and physical contact are presented. Experimental data are presented from a study comparing attending surgeons and surgery residents.ResultsAnalysis shows force metrics (absolute maximum force/torque in z-direction), motion metrics (yaw, pitch, roll), physical contact metric, and image-enabled force metrics (orthogonal and tangential forces) are found to be statistically significant in differentiating suturing skill between attendings and residents.Conclusion and significanceThe results suggest that this simulator and accompanying metrics could serve as a useful tool for assessing and teaching open surgery suturing skill.

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