Yüksek LisansAçık Erişim

Otonom sütur için doku kesiği, sütur iğnesi, ve sütur ipliğinin çoklu kamera akışında görsel yerelleştirilmesi

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2024
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Özet (EN)

Autonomous suturing systems could potentially replace the surgeon in suturing and benefit both patient and surgeon. Automating the suturing process involves many complex challenges and this paper proposes a comprehensive solution to the localization problems. In this context, localization problems refer to the challenges involved in the visual tracking of suture needle, suture thread, and tissue, which are fundamental processes for autonomous suturing that must be robust, precise, and computationally affordable. Surgical instruments' reflective, superfine, or non-rigid structures make their localization a complex problem. The contribution of this study is that it provides a combined algorithm for suture needle and thread detection, an algorithm for tissue cut detection. The overall localization approach proposed here defines the suture needle and its thread with fewer parameters, enabling a more precise and less computationally intensive localization. For the testing of the proposed approach, an experimental setup featuring two 7-DOF robots equipped with surgical instruments and two fully calibrated cameras were utilized. The localization experiments were done using realistic artificial (silicone) tissues and threaded surgical needles. The results of the experiments validated that the proposed method meets the requirements for performing automated robotic sutures.

Yazar

Murat Özvin

Bu Yayına Nasıl Atıf Yapılır

Murat Özvin (Master Thesis). Otonom sütur için doku kesiği, sütur iğnesi, ve sütur ipliğinin çoklu kamera akışında görsel yerelleştirilmesi, 2024, Özyeğin University.

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