3 code implementations • 30 Jan 2020 • Max Allan, Satoshi Kondo, Sebastian Bodenstedt, Stefan Leger, Rahim Kadkhodamohammadi, Imanol Luengo, Felix Fuentes, Evangello Flouty, Ahmed Mohammed, Marius Pedersen, Avinash Kori, Varghese Alex, Ganapathy Krishnamurthi, David Rauber, Robert Mendel, Christoph Palm, Sophia Bano, Guinther Saibro, Chi-Sheng Shih, Hsun-An Chiang, Juntang Zhuang, Junlin Yang, Vladimir Iglovikov, Anton Dobrenkii, Madhu Reddiboina, Anubhav Reddy, Xingtong Liu, Cong Gao, Mathias Unberath, Myeonghyeon Kim, Chanho Kim, Chaewon Kim, Hye-Jin Kim, Gyeongmin Lee, Ihsan Ullah, Miguel Luna, Sang Hyun Park, Mahdi Azizian, Danail Stoyanov, Lena Maier-Hein, Stefanie Speidel
In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward kinematics and instrument CAD models.
Video feedback provides a wealth of information about surgical procedures and is the main sensory cue for surgeons.
Surgical simulation is an increasingly important element of surgical education.
After testing an existing face detection trained model, a new dataset tailored to the surgical environment, with faces obstructed by surgical masks and caps, was collected for fine-tuning to achieve higher face-detection rates in the OR.