Automatic situation recognition using endoscopic images and navigation information in endoscopic sinus surgery
Author:
Affiliation:
1. Graduate School of Science and Engineering, Chiba University, Chiba, Japan
2. Center of Frontier Medical Engineering, Chiba University, Chiba, Japan
3. Department of Otorhinolaryngology, The Jikei University School of Medicine, Tokyo, Japan
Publisher
The Japan Society of Computer Aided Surgery
Link
https://www.jstage.jst.go.jp/article/jscas/23/2/23_48/_pdf
Reference17 articles.
1. 3) Sugino T, Nakamura R, Kuboki A, et al. Comparative analysis of surgical processes for image-guided endoscopic sinus surgery. Int J CARS. 2019 Jan 1; 14 (1): 93-104.
2. 4) Yamaguchi. T, Nakamura, R, Kuboki. A, et al. Skill Assessment and Visualization System for Endoscopic Sinus Surgery: a Clinical Study. JJSCAS. 2020; 22 (1): 21-32.
3. 5) A. I. Pernek, A survey of context recognition in surgery. Medical and Biological Engineering and Computing. 2017; 55 (10): 1719-1734.
4. 6) Aksamentov I, Twinanda A. P, Mutter D, et al. Deep Neural Networks Predict Remaining Surgery Duration from Cholecystectomy Videos. Medical Image Computing and Computer-Assisted Intervention. 2017; 10434: 586-593.
5. 7) N. Padoy, T. Blum, S. -A. Ahmadi, et al. Statistical modeling and recognition of surgical workflow. Med. Image Anal. 2012; 16 (3): 632-641.
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1. Improving situation recognition using endoscopic videos and navigation information for endoscopic sinus surgery;International Journal of Computer Assisted Radiology and Surgery;2022-09-23
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