Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Leonardo Tanzi"'
Autor:
Magda Jablonska, João André Sousa, Marc Molina, Pere Canals, Alvaro Garcia‐Tornel, Marc Rodrigo‐Gisbert, Federica Rizzo, Marta Olivé‐Gadea, Manuel Requena, David Rodriguez‐Luna, Noelia Rodriguez‐Villatoro, Jesús M. Juega, Marián Muchada, Jorge Pagola, Marta Rubiera, Alejandro Tomasello, Carlos A. Molina, Leonardo Tanzi, Victor Salvia, Cristian Marti, Marc Ribo
Publikováno v:
Stroke: Vascular and Interventional Neurology, Vol 3, Iss S2 (2023)
Introduction In stroke patients, accurate infarct volume assessment at 24 hours typically requires manual segmentation of lesions that often are not well defined. We aimed to validate an automated machine learning algorithm (MethinksFIV) specifically
Externí odkaz:
https://doaj.org/article/e29d6ea02a7e490fafc6d62f95e122cb
X-Ray Bone Fracture Classification Using Deep Learning: A Baseline for Designing a Reliable Approach
Publikováno v:
Applied Sciences, Vol 10, Iss 4, p 1507 (2020)
In recent years, bone fracture detection and classification has been a widely discussed topic and many researchers have proposed different methods to tackle this problem. Despite this, a universal approach able to classify all the fractures in the hu
Externí odkaz:
https://doaj.org/article/56e8d946971e4e13bb186cf3f5ec3534
Autor:
Marco Martino Rosso, Angelo Aloisio, Vincenzo Randazzo, Leonardo Tanzi, Giansalvo Cirrincione, Giuseppe Carlo Marano
Publikováno v:
Integrated Computer-Aided Engineering. :1-20
In the last decades, the majority of the existing infrastructure heritage is approaching the end of its nominal design life mainly due to aging, deterioration, and degradation phenomena, threatening the safety levels of these strategic routes of comm
Exploiting deep learning and augmented reality in fused deposition modeling: a focus on registration
Publikováno v:
International Journal on Interactive Design and Manufacturing (IJIDeM). 17:103-114
The current study aimed to propose a Deep Learning (DL) based framework to retrieve in real-time the position and the rotation of an object in need of maintenance from live video frames only. For testing the positioning performances, we focused on in
Publikováno v:
Multimedia Tools and Applications.
The 6D pose estimation of an object from an image is a central problem in many domains of Computer Vision (CV) and researchers have struggled with this issue for several years. Traditional pose estimation methods (1) leveraged on geometrical approach
Publikováno v:
Journal of Personalized Medicine
Volume 13
Issue 3
Pages: 413
Volume 13
Issue 3
Pages: 413
The current study presents a multi-task end-to-end deep learning model for real-time blood accumulation detection and tools semantic segmentation from a laparoscopic surgery video. Intraoperative bleeding is one of the most problematic aspects of lap
A deep learning framework for real-time 3D model registration in robot-assisted laparoscopic surgery
Autor:
Erica Padovan, Giorgia Marullo, Leonardo Tanzi, Pietro Piazzolla, Sandro Moos, Francesco Porpiglia, Enrico Vezzetti
Publikováno v:
The international journal of medical robotics + computer assisted surgery : MRCAS. 18(3)
The current study presents a deep learning framework to determine, in real-time, position and rotation of a target organ from an endoscopic video. These inferred data are used to overlay the 3D model of patient's organ over its real counterpart. The
In recent years, the scientific community has focused on the development of CAD tools that could improve bone fractures' classification, mostly based on Convolutional Neural Network (CNN). However, the discerning accuracy of fractures' subtypes was f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca2b1e33ac10ef3c43541a998c9c079a
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery
Purpose 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-ste
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb252431164138efb6610665e2275966
http://hdl.handle.net/11583/2909492
http://hdl.handle.net/11583/2909492
Publikováno v:
The international journal of medical robotics + computer assisted surgery : MRCASREFERENCES. 16(5)
PURPOSE The current study aimed to systematically review the literature addressing the use of deep learning (DL) methods in intraoperative surgery applications, focusing on the data collection, the objectives of these tools and, more technically, the