The current study aimed to propose a Deep Learning (DL) and Augmented Reality (AR) based solution for a in-vivo robot-assisted radical prostatectomy (RARP), to improve the precision of a published work from our group. We implemented a two-steps automatic system to align a 3D virtual ad-hoc model of a patient's organ with its 2D endoscopic image, to assist surgeons during the procedure.

Real-time deep learning semantic segmentation during intra-operative surgery for 3D augmented reality assistance / Tanzi, Leonardo; Piazzolla, Pietro; Porpiglia, Francesco; Vezzetti, Enrico. - In: INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY. - ISSN 1861-6410. - ELETTRONICO. - (2021). [10.1007/s11548-021-02432-y]

Real-time deep learning semantic segmentation during intra-operative surgery for 3D augmented reality assistance

Tanzi, Leonardo;Piazzolla, Pietro;Vezzetti, Enrico
2021

Abstract

The current study aimed to propose a Deep Learning (DL) and Augmented Reality (AR) based solution for a in-vivo robot-assisted radical prostatectomy (RARP), to improve the precision of a published work from our group. We implemented a two-steps automatic system to align a 3D virtual ad-hoc model of a patient's organ with its 2D endoscopic image, to assist surgeons during the procedure.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2909492