Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Alice Segato"'
Publikováno v:
APL Bioengineering, Vol 4, Iss 4, Pp 041503-041503-35 (2020)
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for analyzing complex medical data and extracting meaningful relationships in datasets, for several clinical aims. Specifically, in the brain care domain, seve
Externí odkaz:
https://doaj.org/article/6fe73a431dc8467b87856dc8d3184e10
Autor:
Alice Segato, Valentina Pieri, Alberto Favaro, Marco Riva, Andrea Falini, Elena De Momi, Antonella Castellano
Publikováno v:
Frontiers in Robotics and AI, Vol 6 (2019)
Deep Brain Stimulation (DBS) is a neurosurgical procedure consisting in the stereotactic implantation of stimulation electrodes to specific brain targets, such as deep gray matter nuclei. Current solutions to place the electrodes rely on rectilinear
Externí odkaz:
https://doaj.org/article/d68ef005fc57447fb45b8799411cd1af
Publikováno v:
IEEE Transactions on Medical Robotics and Bionics
Learning-based methods represent the state of the art in path planning problems. Their performance, however, depend on the number of medical images available for the training. Generative Adversarial Networks (GANs) are unsupervised neural networks th
Publikováno v:
Autonomous Robots
Traditional path planning methods, such as sampling-based and iterative approaches, allow for optimal path’s computation in complex environments. Nonetheless, environment exploration is subject to rules which can be obtained by domain experts and c
Autor:
Elena De Momi, Alice Segato
An autonomous robotic laparoscopic surgical technique is capable of tracking tissue motion and offers consistency in suturing for the anastomosis of the small bowel.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66fad0c2d94baf9f1dbc5ef615195656
http://hdl.handle.net/11311/1204920
http://hdl.handle.net/11311/1204920
Publikováno v:
IEEE transactions on bio-medical engineering. 69(6)
This paper presentsa safe and effective keyhole neurosurgery intra-operative planning framework for flexible neurosurgical robots. The framework is intended to support neurosurgeons during the intra-operative procedure to react to a dynamic environme
Autor:
Elena De Momi, Jessica Zangari, Alice Segato, Valentina Corbetta, Francesco Calimeri, Simona Perri
Publikováno v:
Electronic Proceedings in Theoretical Computer Science. 345:236-237
Autor:
Alice Segato, Francesco Calimeri, Jessica Zangari, Valentina Corbetta, Simona Perri, Elena De Momi
Publikováno v:
2021 IEEE International Conference on Robotics and Automation (ICRA)
ICRA
ICRA
Keyhole neurosurgery is challenging, due to the complex anatomy of the brain and the inherent risk of damaging vital structures while reaching the surgical target. This paper presents a path planner for safe and effective neurosurgical interventions.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3923165836cc69b12bffbea9b90db16
http://hdl.handle.net/11311/1172080
http://hdl.handle.net/11311/1172080
Publikováno v:
IEEE Transactions on Robotics
Path planning algorithms for steerable needles in medical applications must guarantee the anatomical obstacle avoidance, reduce the insertion length, and ensure the compliance with the needle kinematics. The majority of the solutions from the literat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c01e0e7b3bc68f777a6ed9e2f1c99ec5
http://hdl.handle.net/11311/1156782
http://hdl.handle.net/11311/1156782
Publikováno v:
Politecnico di Milano-IRIS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d4b28777e95ea969c4e82ff18a3a0977
http://hdl.handle.net/11311/1148211
http://hdl.handle.net/11311/1148211