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结合基于计算机视觉的软件和分布式光纤应变传感器评估普通外科和眼微创手术中的缝合性能:概念验证。

Evaluation of suturing performance in general surgery and ocular microsurgery by combining computer vision-based software and distributed fiber optic strain sensors: a proof-of-concept.

机构信息

Department of Electrical Engineering, Faculty of Engineering, Holon Institute of Technology, Holon, Israel.

Department of Ophthalmology, Rabin Medical Center, Petach Tikva, Israel.

出版信息

Int J Comput Assist Radiol Surg. 2020 Aug;15(8):1359-1367. doi: 10.1007/s11548-020-02187-y. Epub 2020 May 10.

Abstract

PURPOSE

Improper suturing may cause an inadequate wound healing process and wound dehiscence as well as infection and even graft rejection in case of corneal transplantation. Hence, training surgeons in correct suturing procedures and objectively assessing their surgical skills is desirable.

METHODS

Two complementary methods for assessment of suturing skills in two medical fields (general surgery and ocular microsurgery) were demonstrated. Suturing quality is assessed by computer vision software. Evaluation of stitching flow of operation is based on measuring strain induced in an optical fiber that is placed in proximity to the wound and parallel thereto and is pressed and passed by wound stitches.

RESULTS

Our software generated a score for suturing outcome in both general surgery and ocular microsurgery when the stitching was done on a patch. Every trainee received a score in the range 0-100 that describes his/her performance. Strain values were recognized when using a patch in general surgery and a rubber patch in ocular microsurgery, but were less distinct in (disqualified) human cornea.

CONCLUSIONS

We proved a concept of an objective scoring method (based on various image processing algorithms) for assessment of suturing performance. It was also shown that fiber optic strain sensors are sensitive to the flow of stitching operation on a patch but are less sensitive to the flow of stitching operation on a human cornea. By combining these two methods, we can comprehensively evaluate the suturing performance objectively.

摘要

目的

在角膜移植中,如果缝合不当,可能会导致伤口愈合过程不充分、伤口裂开以及感染,甚至移植物排斥。因此,有必要培训外科医生正确的缝合技术,并客观评估他们的手术技能。

方法

展示了两种用于评估两个医学领域(普通外科和眼科显微手术)缝合技能的互补方法。通过计算机视觉软件评估缝合质量。操作缝线流动的评估是基于测量放置在伤口附近并与之平行的光纤中产生的应变,该光纤被伤口缝线压过并穿过。

结果

当在补丁上进行缝合时,我们的软件在普通外科和眼科显微手术中都为缝合结果生成了一个分数。每个学员的得分都在 0-100 之间,描述了他/她的表现。在普通外科中使用补丁和在眼科显微手术中使用橡胶补丁时,可以识别出应变值,但在(不合格的)人角膜中则不太明显。

结论

我们证明了一种客观评分方法的概念(基于各种图像处理算法),用于评估缝合性能。还表明,光纤应变传感器对补丁上缝线操作的流动敏感,但对人角膜上缝线操作的流动不太敏感。通过结合这两种方法,我们可以全面客观地评估缝合性能。

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