Stereo Correspondence and Reconstruction of Endoscopic Data Challenge

The stereo correspondence and reconstruction of endoscopic data sub-challenge was organized during the Endovis challenge at MICCAI 2019 in Shenzhen, China. The task was to perform dense depth estimation using 7 training datasets and 2 test sets of structured light data captured using porcine cadavers. These were provided by a team at Intuitive Surgical. 10 teams participated in the challenge day. This paper contains 3 additional methods which were submitted after the challenge finished as well as a supplemental section from these teams on issues they found with the dataset.

[1]  Thomas Brox,et al.  A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[3]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[4]  Michael Happold,et al.  Hierarchical Deep Stereo Matching on High-Resolution Images , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Yang Hu,et al.  Endoscopic Depth Measurement and Super-Spectral-Resolution Imaging , 2017, MICCAI.

[6]  Nazim Haouchine,et al.  Image-guided simulation of heterogeneous tissue deformation for augmented reality during hepatic surgery , 2013, 2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR).

[7]  Jan Kautz,et al.  PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[8]  Yinda Zhang,et al.  Deep Depth Completion of a Single RGB-D Image , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[9]  Ryan S. Decker,et al.  Supervised autonomous robotic soft tissue surgery , 2016, Science Translational Medicine.

[10]  P. Eisert,et al.  Joint Estimation of Epipolar Geometry and Rectification Parameters using Point Correspondences for Stereoscopic TV Sequences , 2010 .

[11]  Richard J. Chen,et al.  Polyp segmentation and classification using predicted depth from monocular endoscopy , 2019, Medical Imaging.

[12]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[13]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Guang-Zhong Yang,et al.  Self-Supervised Siamese Learning on Stereo Image Pairs for Depth Estimation in Robotic Surgery , 2017, ArXiv.

[15]  Guang-Zhong Yang,et al.  Real-Time Stereo Reconstruction in Robotically Assisted Minimally Invasive Surgery , 2010, MICCAI.

[16]  Peter Eisert,et al.  Semantic Kernels Binarized - A Feature Descriptor for Fast and Robust Matching , 2011, 2011 Conference for Visual Media Production.

[17]  Xiaogang Wang,et al.  Group-Wise Correlation Stereo Network , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[18]  Danail Stoyanov,et al.  OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis , 2018, Lecture Notes in Computer Science.

[19]  Richard Szeliski,et al.  High-accuracy stereo depth maps using structured light , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[20]  Rui Hu,et al.  DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[21]  Andreas Geiger,et al.  Vision meets robotics: The KITTI dataset , 2013, Int. J. Robotics Res..

[22]  Peter Eisert,et al.  Real-time 3D body reconstruction for immersive TV , 2016, 2016 IEEE International Conference on Image Processing (ICIP).

[23]  Dragomir Anguelov,et al.  Scalability in Perception for Autonomous Driving: Waymo Open Dataset , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[24]  Guang-Zhong Yang,et al.  Practical Intraoperative Stereo Camera Calibration , 2014, MICCAI.