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Valentina Corbetta

dblp:304/4141 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Motion planning and robot control · 33% Planning, search and constraint satisfaction · 33% Robot navigation and mapping · 33%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping
obstacle avoidance
0.512021
Optimized 3D path planner for steerable catheters with deductive reasoning · ICRA 2021
Robotics › Motion planning and robot control
path planning
0.512021
Optimized 3D path planner for steerable catheters with deductive reasoning · ICRA 2021
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning under uncertainty
risk-aware planning
0.512021
Optimized 3D path planner for steerable catheters with deductive reasoning · ICRA 2021

Methods — techniques the papers use, named apart from their topics

deductive reasoning · 1.03d visualization · 1.0
YearPublicationVenuePosition
2021 Optimized 3D path planner for steerable catheters with deductive reasoning
abstract
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. The strengths of the proposed framework lay in the integration of multiple risk structures combined into a deductive method for fast and intuitive user interaction, and a modular architecture. The tool is intended to support neurosurgeons at quickly determining the most appropriate surgical trajectory through the brain matter with minimized risk; the user interface guides the user through the decision making process and helps save planning time of neurosurgical interventions. Risk structures and trajectories can be visualized in an intuitive way, thanks to a 3D brain surgery simulator developed with Unity. A qualitative evaluation with clinical experts shows the practical relevance, while a quantitative performance and functionality analysis proves the robustness and effectiveness of the system with respect to literature.
Alice Segato, Valentina Corbetta, Jessica Zangari, Simona Perri, Francesco Calimeri, Elena De Momi
ICRA2