Andrea Novaresio
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Andrea Novaresio has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Enrico Vezzetti
Department of Management and Production Engineering, Politecnico di Torino, 10129 Turin, Italy
2 shared publications - Sandro Moos
Politecnico di Torino
2 shared publications - Alessandro Carpinello
Division of Maxillofacial Surgery, Surgical Science Department, Città della Salute e della Scienza Hospital, University of Torino, 10124 Torino, Italy
1 shared publication - Claudia Borbon
Division of Maxillofacial Surgery, Città della Salute e della Scienza University Hospital, 10126 Torino, Italy
1 shared publication - Emanuele Zavattero
Division of Maxillofacial Surgery, Città della Salute e della Scienza Hospital, University of Turin, c.so Dogliotti 14, 10126 Turin, Italy
1 shared publication - Federico Salerno
Politecnico di Torino
1 shared publication
Latest Publications
- 7 February 2024
- Published by Springer Nature
- p. 184-193
A Methodology for the Dimensional and Mechanical Analysis of Surgical Guides
- 7 February 2024
- Published by Springer Nature
- p. 184-193
A Methodology for the Dimensional and Mechanical Analysis of Surgical Guides
- Open Access
- 22 November 2021
- Published by MDPI AG in Applied Sciences
- Vol. 11 (22) , 11053
Evaluation of HMDs by QFD for Augmented Reality Applications in the Maxillofacial Surgery Domain
Today, surgical operations are less invasive than they were a few decades ago and, in medicine, there is a growing trend towards precision surgery. Among many technological advancements, augmented reality (AR) can be a powerful tool for improving the surgery practice through its ability to superimpose the 3D geometrical information of the pre-planned operation over the surgical field as well as medical and instrumental information gathered from operating room equipment. AR is fundamental to reach new standards in maxillofacial surgery. The surgeons will be able to not shift their focus from the patients while looking to the monitors. Osteotomies will not require physical tools to be fixed on patient bones as guides to make resections. Handling grafts and 3D models directly in the operating room will permit a fine tuning of the procedure before harvesting the implant. This article aims to study the application of AR head-mounted displays (HMD) in three operative scenarios (oncological and reconstructive surgery, orthognathic surgery, and maxillofacial trauma surgery) by the means of quantitative logic using the Quality Function Deployment (QFD) tool to determine their requirements. The article provides an evaluation of the readiness degree of HMD currently on market and highlights the lacking features.
- 22 November 2021
- Published by MDPI AG in Applied Sciences
- Vol. 11 (22) , 11053
Open AccessEvaluation of HMDs by QFD for Augmented Reality Applications in the Maxillofacial Surgery Domain
Today, surgical operations are less invasive than they were a few decades ago and, in medicine, there is a growing trend towards precision surgery. Among many technological advancements, augmented reality (AR) can be a powerful tool for improving the surgery practice through its ability to superimpose the 3D geometrical information of the pre-planned operation over the surgical field as well as medical and instrumental information gathered from operating room equipment. AR is fundamental to reach new standards in maxillofacial surgery. The surgeons will be able to not shift their focus from the patients while looking to the monitors. Osteotomies will not require physical tools to be fixed on patient bones as guides to make resections. Handling grafts and 3D models directly in the operating room will permit a fine tuning of the procedure before harvesting the implant. This article aims to study the application of AR head-mounted displays (HMD) in three operative scenarios (oncological and reconstructive surgery, orthognathic surgery, and maxillofacial trauma surgery) by the means of quantitative logic using the Quality Function Deployment (QFD) tool to determine their requirements. The article provides an evaluation of the readiness degree of HMD currently on market and highlights the lacking features.