2020 CATARACTS Semantic Segmentation Challenge

no code implementations • 21 Oct 2021 • Imanol Luengo, Maria Grammatikopoulou, Rahim Mohammadi, Chris Walsh, Chinedu Innocent Nwoye, Deepak Alapatt, Nicolas Padoy, Zhen-Liang Ni, Chen-Chen Fan, Gui-Bin Bian, Zeng-Guang Hou, Heonjin Ha, Jiacheng Wang, Haojie Wang, Dong Guo, Lu Wang, Guotai Wang, Mobarakol Islam, Bharat Giddwani, Ren Hongliang, Theodoros Pissas, Claudio Ravasio, Martin Huber, Jeremy Birch, Joan M. Nunez Do Rio, Lyndon Da Cruz, Christos Bergeles, Hongyu Chen, Fucang Jia, Nikhil KumarTomar, Debesh Jha, Michael A. Riegler, Pal Halvorsen, Sophia Bano, Uddhav Vaghela, Jianyuan Hong, Haili Ye, Feihong Huang, Da-Han Wang, Danail Stoyanov

In 2020, we released pixel-wise semantic annotations for anatomy and instruments for 4670 images sampled from 25 videos of the CATARACTS training set.

Anatomy Scene Segmentation

Robust Medical Instrument Segmentation Challenge 2019

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.

Benchmarking Instance Segmentation +1

BARNet: Bilinear Attention Network with Adaptive Receptive Fields for Surgical Instrument Segmentation

no code implementations • 20 Jan 2020 • Zhen-Liang Ni, Gui-Bin Bian, Guan-An Wang, Xiao-Hu Zhou, Zeng-Guang Hou, Xiao-Liang Xie, Zhen Li, Yu-Han Wang

For the scale variation, our adaptive receptive field module aggregates multi-scale features and automatically fuses them with different weights.

Semantic Segmentation

Attention-Guided Lightweight Network for Real-Time Segmentation of Robotic Surgical Instruments

1 code implementation • 24 Oct 2019 • Zhen-Liang Ni, Gui-Bin Bian, Zeng-Guang Hou, Xiao-Hu Zhou, Xiao-Liang Xie, Zhen Li

LWANet adopts encoder-decoder architecture, where the encoder is the lightweight network MobileNetV2, and the decoder consists of depthwise separable convolution, attention fusion block, and transposed convolution.

RAUNet: Residual Attention U-Net for Semantic Segmentation of Cataract Surgical Instruments

1 code implementation • 23 Sep 2019 • Zhen-Liang Ni, Gui-Bin Bian, Xiao-Hu Zhou, Zeng-Guang Hou, Xiao-Liang Xie, Chen Wang, Yan-Jie Zhou, Rui-Qi Li, Zhen Li

To the best of our knowledge, this is the first cataract surgical instrument dataset for semantic segmentation.

Semantic Segmentation

RASNet: Segmentation for Tracking Surgical Instruments in Surgical Videos Using Refined Attention Segmentation Network

1 code implementation • 21 May 2019 • Zhen-Liang Ni, Gui-Bin Bian, Xiao-Liang Xie, Zeng-Guang Hou, Xiao-Hu Zhou, Yan-Jie Zhou

The dataset from the MICCAI EndoVis Challenge 2017 is used to evaluate our network.

Transfer Learning