Automatic localization of the da Vinci surgical instrument tips in 3D transrectal ultrasound - Abstract

Robot-Assisted Laparoscopic Radical Prostatectomy (RALRP) using the da Vinci surgical system is the current state of the art treatment option for clinically confined prostate cancer.

Given the limited field of view of the surgical site in RALRP, several groups have proposed the integration of transrectal ultrasound (TRUS) imaging in the surgical workflow to assist with accurate resection of the prostate and the sparing of the neuro-vascular bundles (NVB). We previously introduced a robotic TRUS manipulator, and a method for automatically tracking da Vinci surgical instruments with the TRUS imaging plane, in order to facilitate the integration of intraoperative TRUS in RALRP [1]. Rapid and automatic registration of the kinematic frames of the da Vinci surgical system and the robotic TRUS probe manipulator is a critical component of the instrument tracking system. In this paper, we propose a fully automatic registration technique based on automatic 3D TRUS localization of robot instrument tips pressed against the air-tissue boundary anterior to the prostate. The detection approach uses a multi-scale filtering technique to identify and localize surgical instrument tips in the TRUS volume, and could also be used to detect other surface fiducials in 3D ultrasound. Experiments have been performed using a tissue phantom and two ex vivo tissue samples to show the feasibility of the proposed methods. Also, an initial in vivo evaluation of the system has been carried out on a live anaesthetized dog with a da Vinci Si surgical system and a target registration error (defined as the root mean square distance of corresponding points after registration) of 2.68 mm has been achieved. Results show this method's accuracy and consistency for automatic registration of TRUS images to the da Vinci surgical system.

Written by:
Mohareri O, Ramezani M, Adebar T, Abolmaesumi P, Salcudean T.   Are you the author?

Reference: IEEE Trans Biomed Eng. 2013 May 13. Epub ahead of print.


PubMed Abstract
PMID: 23674418

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