1 code implementation • 4 Jul 2022 • Negin Ghamsarian, Mario Taschwer, Raphael Sznitman, Klaus Schoeffmann
Semantic segmentation in cataract surgery has a wide range of applications contributing to surgical outcome enhancement and clinical risk reduction.
no code implementations • 25 Sep 2021 • Negin Ghamsarian, Mario Taschwer, Doris Putzgruber-Adamitsch, Stephanie Sarny, Yosuf El-Shabrawi, Klaus Schoeffmann
Semantic segmentation in surgical videos is a prerequisite for a broad range of applications towards improving surgical outcomes and surgical video analysis.
no code implementations • 11 Sep 2021 • Negin Ghamsarian, Mario Taschwer, Klaus Schoeffmann
This paper proposes a semantic segmentation network termed as DeepPyram that can achieve superior performance in segmenting relevant objects in cataract surgery videos with varying issues.
1 code implementation • 2 Jul 2021 • Negin Ghamsarian, Mario Taschwer, Doris Putzgruber-Adamitsch, Stephanie Sarny, Yosuf El-Shabrawi, Klaus Schoeffmann
In particular, we propose (I) an end-to-end recurrent neural network to recognize the lens-implantation phase and (II) a novel semantic segmentation network to segment the lens and pupil after the implantation phase.
no code implementations • 29 Apr 2021 • Negin Ghamsarian, Mario Taschwer, Doris Putzgruber-Adamitsch, Stephanie Sarny, Klaus Schoeffmann
This module consists of four parallel recurrent CNNs being responsible to detect four relevant phases that have been defined with medical experts.
no code implementations • 23 Mar 2020 • Tobias Ross, Annika Reinke, Peter M. Full, Martin Wagner, Hannes Kenngott, Martin Apitz, Hellena Hempe, Diana Mindroc Filimon, Patrick Scholz, Thuy Nuong Tran, Pierangela Bruno, Pablo Arbeláez, Gui-Bin Bian, Sebastian Bodenstedt, Jon Lindström Bolmgren, Laura Bravo-Sánchez, Hua-Bin Chen, Cristina González, Dong Guo, Pål Halvorsen, Pheng-Ann Heng, Enes Hosgor, Zeng-Guang Hou, Fabian Isensee, Debesh Jha, Tingting Jiang, Yueming Jin, Kadir Kirtac, Sabrina Kletz, Stefan Leger, Zhixuan Li, Klaus H. Maier-Hein, Zhen-Liang Ni, Michael A. Riegler, Klaus Schoeffmann, Ruohua Shi, Stefanie Speidel, Michael Stenzel, Isabell Twick, Gutai Wang, Jiacheng Wang, Liansheng Wang, Lu Wang, Yu-Jie Zhang, Yan-Jie Zhou, Lei Zhu, Manuel Wiesenfarth, Annette Kopp-Schneider, Beat P. Müller-Stich, Lena Maier-Hein
The validation of the competing methods for the three tasks (binary segmentation, multi-instance detection and multi-instance segmentation) was performed in three different stages with an increasing domain gap between the training and the test data.