Chapter title |
Eye-gaze driven surgical workflow segmentation.
|
---|---|
Chapter number | 14 |
Book title |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007
|
Published in |
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, January 2007
|
DOI | 10.1007/978-3-540-75759-7_14 |
Pubmed ID | |
Book ISBNs |
978-3-54-075758-0, 978-3-54-075759-7
|
Authors |
A. James, D. Vieira, B. Lo, A. Darzi, G. -Z. Yang, James, A., Vieira, D., Lo, B., Darzi, A., Yang, G. -Z. |
Abstract |
In today's climate of clinical governance there is growing pressure on surgeons to demonstrate their competence, improve standards and reduce surgical errors. This paper presents a study on developing a novel eye-gaze driven technique for surgical assessment and workflow recovery. The proposed technique investigates the use of a Parallel Layer Perceptor (PLP) to automate the recognition of a key surgical step in a porcine laparoscopic cholecystectomy model. The classifier is eye-gaze contingent but combined with image based visual feature detection for improved system performance. Experimental results show that by fusing image instrument likelihood measures, an overall classification accuracy of 75% is achieved. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 2 | 4% |
Slovenia | 1 | 2% |
Unknown | 52 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 14 | 25% |
Researcher | 11 | 20% |
Student > Master | 6 | 11% |
Student > Bachelor | 4 | 7% |
Professor > Associate Professor | 4 | 7% |
Other | 9 | 16% |
Unknown | 7 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 17 | 31% |
Engineering | 13 | 24% |
Medicine and Dentistry | 6 | 11% |
Agricultural and Biological Sciences | 1 | 2% |
Psychology | 1 | 2% |
Other | 6 | 11% |
Unknown | 11 | 20% |