Surgical Phase Recognition: From Public Datasets to Real-World Data

Autor: Kadir Kirtac, Nizamettin Aydin, Joël L. Lavanchy, Guido Beldi, Marco Smit, Michael S. Woods, Florian Aspart

Publikováno v: Applied Sciences, Vol 12, Iss 17, p 8746 (2022)

Automated recognition of surgical phases is a prerequisite for computer-assisted analysis of surgeries. The research on phase recognition has been mostly driven by publicly available datasets of laparoscopic cholecystectomy (Lap Chole) videos. Yet, v

Externí odkaz: https://doaj.org/article/cd638bc34c2e4ce48acc163351c30dac

Automation of surgical skill assessment using a three-stage machine learning algorithm

Autor: Guido Beldi, Isabell Twick, Joel Zindel, Joël L. Lavanchy, Daniel Candinas, Enes Hosgor, Kadir Kirtac

Publikováno v: Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Scientific Reports
Lavanchy, Joël L.; Zindel, Joel; Kirtac, Kadir; Twick, Isabell; Hosgor, Enes; Candinas, Daniel; Beldi, Guido (2021). Automation of surgical skill assessment using a three-stage machine learning algorithm. Scientific reports, 11(1) Springer Nature 10.1038/s41598-021-84295-6

Surgical skills are associated with clinical outcomes. To improve surgical skills and thereby reduce adverse outcomes, continuous surgical training and feedback is required. Currently, assessment of surgical skills is a manual and time-consuming proc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d247ccef6f7bf5384eb140669b1459e7
https://doaj.org/article/dc51263bc4504396ad577f84e95bb043

Author Correction: Automation of surgical skill assessment using a three-stage machine learning algorithm

Autor: Isabell Twick, Guido Beldi, Daniel Candinas, Kadir Kirtac, Joel Zindel, Joël L. Lavanchy, Enes Hosgor

Publikováno v: Scientific Reports, Vol 11, Iss 1, Pp 1-1 (2021)
Lavanchy, Joël L.; Zindel, Joel; Kirtac, Kadir; Twick, Isabell; Hosgor, Enes; Candinas, Daniel; Beldi, Guido (2021). Author Correction: Automation of surgical skill assessment using a three-stage machine learning algorithm. Scientific Reports, 11(1), p. 8933. Nature Publishing Group 10.1038/s41598-021-88175-x

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a7bb09aea80fb3675997afc81c256a1
https://doi.org/10.1038/s41598-021-88175-x

How Image Degradations Affect Deep CNN-based Face Recognition?

Autor: Hazim Kemal Ekenel, Ferhat Sukru Rende, Merve Kilinc Yildirum, Kadir Kirtac, Gultekin Butun, Samil Karahan

Publikováno v: BIOSIG

Face recognition approaches that are based on deep convolutional neural networks (CNN) have been dominating the field. The performance improvements they have provided in the so called in-the-wild datasets are significant, however, their performance u

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fd970afe482f136abfdcf07f4e33fde