Papers

10

Total Citations

156

H-Index

8

About

Samaneh Azargoshasb is a multidisciplinary researcher whose work bridges robotics, surgical guidance technologies, and human-robot interaction. Her most impactful contributions lie at the intersection of robot-assisted surgery and intraoperative imaging, where she has pioneered advances in radioguided and fluorescence-guided surgical systems. Her highly cited 2022 study on signal-to-background ratios in fluorescence-guided surgery (40 citations) established critical quantitative frameworks for distinguishing cancerous lesions intraoperatively, directly informing the development of next-generation surgical tracers. Azargoshasb has been a key contributor to the DROP-IN gamma probe ecosystem, advancing tethered robotic detection tools — including the Click-On gamma probe — that enhance surgical dexterity and decision-making in minimally invasive urologic procedures. Her integration of optical navigation and AI-supported video analysis into robotic radioguided surgery reflects a commitment to smarter, data-driven operating rooms. Alongside this surgical focus, her earlier work in voice command recognition and sound source localization for human-robot interaction demonstrates foundational expertise in intelligent robotic systems. With over 130 cumulative citations across a decade of research, Azargoshasb's portfolio positions her as an emerging leader in the convergence of nuclear medicine, robotics, and surgical innovation.

Research Focus

Key Achievements

8
H-Index
10
Papers
156
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Quantifying the Impact of Signal-to-background Ratios on Surgical Discrimination of Fluorescent Lesions
40 citations · 2022
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 34
🏛 Institutions: Leiden University Medical Center, Iran University of Science and Technology, University of Shahrood

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago