A novel dual-network architecture for mixed-supervised medical image segmentation
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Jagadeesan Jayender | Nir Ben-Shlomo | Yu Cheng | Duo Wang | Ming Li | C. Eduardo Corrales | Tao Zhang | J. Jayender | Duo Wang | Ming Li | C. Corrales | Tao Zhang | N. Ben-Shlomo | Yu Cheng
[1] Bastian Leibe,et al. Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] S. N. Merchant,et al. MS-Net: Mixed-Supervision Fully-Convolutional Networks for Full-Resolution Segmentation , 2018, MICCAI.
[3] Fei-Fei Li,et al. What's the Point: Semantic Segmentation with Point Supervision , 2015, ECCV.
[4] Kaiming He,et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] Huimin Ma,et al. Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[6] Iasonas Kokkinos,et al. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] Joseph O. Deasy,et al. Multiple Resolution Residually Connected Feature Streams for Automatic Lung Tumor Segmentation From CT Images , 2019, IEEE Transactions on Medical Imaging.
[8] Jing Wang,et al. Walk and Learn: Facial Attribute Representation Learning from Egocentric Video and Contextual Data , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Hao Chen,et al. DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Youbao Tang,et al. Accurate Weakly-Supervised Deep Lesion Segmentation using Large-Scale Clinical Annotations: Slice-Propagated 3D Mask Generation from 2D RECIST , 2018, MICCAI.
[11] W. Wells,et al. Deep Learning–Based Automatic Segmentation of Lumbosacral Nerves on CT for Spinal Intervention: A Translational Study , 2019, American Journal of Neuroradiology.
[12] Stephen J. McKenna,et al. Boundary-Aware Fully Convolutional Network for Brain Tumor Segmentation , 2017, MICCAI.
[13] Yu Cheng,et al. Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[14] Konstantinos Kamnitsas,et al. DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks , 2016, IEEE Transactions on Medical Imaging.
[15] Ross B. Girshick,et al. Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[16] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Seyed-Ahmad Ahmadi,et al. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation , 2016, 2016 Fourth International Conference on 3D Vision (3DV).
[18] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[19] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[20] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[21] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Eric Granger,et al. Constrained‐CNN losses for weakly supervised segmentation☆ , 2018, Medical Image Anal..
[23] Ali Farhadi,et al. You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Nassir Navab,et al. Recalibrating Fully Convolutional Networks With Spatial and Channel “Squeeze and Excitation” Blocks , 2018, IEEE Transactions on Medical Imaging.
[25] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[26] Ross B. Girshick,et al. Mask R-CNN , 2017, 1703.06870.
[27] Enhua Wu,et al. Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[28] Nassir Navab,et al. Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks , 2018, MICCAI.
[29] Bram van Ginneken,et al. A survey on deep learning in medical image analysis , 2017, Medical Image Anal..