Sensors and Artificial Intelligence for Surgery Augmentation
Contents
Chair(s)
Prof. Michael Friebe
Department of Measurement and Electronics, AGH University of Science and Technology, Kraków, Poland.
Dr. Alfredo Illanes
INKA-Application Driven Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Speaker(s)
Nazila Esmaeili, M. Sc
Department of Otorhinolaryngology, Head and Neck Surgery, Faculty of Medicine, Justus Liebig University of Giessen, Hesse, Germany.
Dr. Axel Boese
INKA Innovation Laboratory for Image Guided Therapy, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Dr. Matthias Seibold
Research in Orthopedic Computer Science (ROCS), Balgrist University Hospital, University of Zurich, Balgrist Campus, Zurich, Switzerland.
Sasan Matinfar, M. Sc.
Computer Aided Medical Procedures (CAMP), Technical University of Munich, München, Germany.
Programme
Programme
- Time
- Speakers
- Topic
- 16:30-16:35
- Michael Friebe /Alfredo Illanes
- Introduction and Welcoming Speech
- 16:35-16:45
- Michael Friebe
- Technology Convergence and Double Exponential Development Speed - Fear and Opportunities!
- 16:30-16:45
- Axel Boese
- Analyze it like a Radiologist: Fluorescence Imaging Quantification for AI
- 17:00-17:15
- Nazila Esmaeili
- Seeing Beyond the Surface: AI-enhanced Contact Endoscopy - Narrow Band Imaging for Laryngeal Lesion Assessment
- 17:15-17:30
- Alfredo Illanes
- Machine Learning-based Vibro-acoustic Classification of Tissue-instrument-interactions for Surgery Augmentation
- 17:30-17:45
- Matthias Seibold
- Deep Learning-based Acoustic Sensing for Orthopedic Interventions
- 17:45-18:00
- Sasan Matinfar
- Sonification in Minimally Invasive Surgery
Moments
Presentation
Technology Convergence and Double Exponential Development Speed - Fear and Opportunities!
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Analyze it like a Radiologist: Fluorescence Imaging Quantification for AI
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Seeing Beyond the Surface: AI-enhanced Contact Endoscopy - Narrow Band Imaging for Laryngeal Lesion Assessment
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Machine Learning-based Vibro-acoustic Classification of Tissue-instrument-interactions for Surgery Augmentation
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Deep Learning-based Acoustic Sensing for Orthopedic Interventions
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Sonification in Minimally Invasive Surgery
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