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智能血管检测系统在腹腔镜手术中的应用

Smart Blood Vessel Detection System for Laparoscopic Surgery.

机构信息

Department of UrologyKaohsiung Medical University Chung-Ho Memorial Hospital Kaohsiung 80756 Taiwan.

Department of Computer Science and Information EngineeringNational Taipei University New Taipei City 237303 Taiwan.

出版信息

IEEE J Transl Eng Health Med. 2022 Mar 11;10:2500207. doi: 10.1109/JTEHM.2022.3159095. eCollection 2022.

Abstract

OBJECTIVE

Compared with traditional surgery, laparoscopic surgery offers the advantages of smaller scars and rapid recovery and has gradually become popular. However, laparoscopic surgery has the limitation of low visibility and a lack of touch sense. As such, a physician may unexpectedly damage blood vessels, causing massive bleeding. In clinical settings, Doppler ultrasound is commonly used to detect vascular locations, but this approach is affected by the measuring angle and bone shadow and has poor ability to distinguish arteries from veins. To tackle these problems, a smart blood vessel detection system for laparoscopic surgery is proposed.

METHODS

Based on the principle of near-infrared spectroscopy, the proposed instrument can access hemoglobin (HbT) parameters at several depths simultaneously and recognize human tissue type by using a neural network.

RESULTS

Using the differences in HbT and StO between different tissues, vascular and avascular locations can be recognized. Moreover, a mechanically rotatable stick enables the physician to easily operate in body cavities. Phantom and animal experiments were performed to validate the system's performance.

CONCLUSION

The proposed system has high ability to distinguish vascular from avascular locations at various depths.

摘要

目的

与传统手术相比,腹腔镜手术具有创伤小、恢复快等优点,逐渐受到青睐。但腹腔镜手术存在视野不佳、缺乏触觉感知的局限性,术者可能会意外损伤血管,导致大出血。在临床中,常采用多普勒超声来探测血管位置,但这种方法易受测量角度和骨骼阴影的影响,且对动脉和静脉的区分能力较差。针对这些问题,本文提出一种用于腹腔镜手术的智能血管探测系统。

方法

该仪器基于近红外光谱原理,可同时获取几个深度的血红蛋白(HbT)参数,并使用神经网络识别人体组织类型。

结果

利用不同组织间 HbT 和 StO 的差异,可以识别血管和非血管位置。此外,仪器的机械可旋转棒可使术者轻松在体腔中操作。通过对离体组织和动物实验进行验证,该系统具有在不同深度区分血管和非血管位置的能力。

结论

该系统具有在不同深度区分血管和非血管位置的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c21/8939714/c3b9f640272d/lin1ab-3159095.jpg

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