1 code implementation • 26 Jul 2021 • Daniil Pakhomov, Sanchit Hira, Narayani Wagle, Kemar E. Green, Nassir Navab
Derived regions are consistent across different images and coincide with human-defined semantic classes on some datasets.
no code implementations • 12 Jul 2021 • Sanchit Hira, Ritwik Das, Abhinav Modi, Daniil Pakhomov
In this work, we present our results on the ARID dataset.
no code implementations • 9 Jul 2020 • Daniil Pakhomov, Wei Shen, Nassir Navab
Surgical tool segmentation in endoscopic images is an important problem: it is a crucial step towards full instrument pose estimation and it is used for integration of pre- and intra-operative images into the endoscopic view.
no code implementations • 8 Jul 2020 • Daniil Pakhomov, Nassir Navab
To account for reduced accuracy of the discovered light-weight deep residual network and avoid adding any additional computational burden, we perform a differentiable search over dilation rates for residual units of our network.
no code implementations • 7 May 2018 • Sebastian Bodenstedt, Max Allan, Anthony Agustinos, Xiaofei Du, Luis Garcia-Peraza-Herrera, Hannes Kenngott, Thomas Kurmann, Beat Müller-Stich, Sebastien Ourselin, Daniil Pakhomov, Raphael Sznitman, Marvin Teichmann, Martin Thoma, Tom Vercauteren, Sandrine Voros, Martin Wagner, Pamela Wochner, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel
The paper presents a comparative validation study of different vision-based methods for instrument segmentation and tracking in the context of robotic as well as conventional laparoscopic surgery.
1 code implementation • 24 Mar 2017 • Daniil Pakhomov, Vittal Premachandran, Max Allan, Mahdi Azizian, Nassir Navab
Detection, tracking, and pose estimation of surgical instruments are crucial tasks for computer assistance during minimally invasive robotic surgery.