Abstract
In this paper the Hidden Markov Models (HMMs) are used as a tool for understanding minimally invasive surgical performance and human factors that characterize it In our experiments we studied data concerning the tools positioning during exercises performed on a surgical simulator. By means of Hidden Markov Models theory, we created a model of the "expert surgeon performance" able to evaluate surgical capability and to distinguish expert and novice surgeon performances. By analyzing the trained model and video acquisitions, we show that it is possible to deduce information about features characterizing the surgical expertise.
Original language | English |
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Pages (from-to) | 445-447 |
Number of pages | 3 |
Journal | International journal of computer assisted radiology and surgery |
Volume | 1 |
Issue number | SUPPL. 7 |
DOIs | |
Publication status | Published - Jun 2006 |
Keywords
- Hidden Markov Model
- Minimally invasive surgery
- Performance evaluation
- Surgical simulator
- Surgical training
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Transplantation