ANU-Net: Attention-based nested U-Net to exploit full resolution features for medical image segmentation
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Chen Li | Wei Chen | Yusong Tan | Fei Li | Xin Luo | Yuanming Gao | Yulin He | Wei Chen | Yuanming Gao | Fei Li | Chen Li | Yusong Tan | Yulin He | Xin Luo
[1] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] 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.
[3] Qingjie Liu,et al. Road Extraction by Deep Residual U-Net , 2017, IEEE Geoscience and Remote Sensing Letters.
[4] Ronan Collobert,et al. Learning to Segment Object Candidates , 2015, NIPS.
[5] Wenyu Liu,et al. Deep patch learning for weakly supervised object classification and discovery , 2017, Pattern Recognit..
[6] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[7] Xiaogang Wang,et al. Pyramid Scene Parsing Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Nima Tajbakhsh,et al. UNet++: A Nested U-Net Architecture for Medical Image Segmentation , 2018, DLMIA/ML-CDS@MICCAI.
[9] Ronald M. Summers,et al. DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation , 2015, MICCAI.
[10] Hayit Greenspan,et al. Fully Convolutional Network for Liver Segmentation and Lesions Detection , 2016, LABELS/DLMIA@MICCAI.
[11] Yoshua Bengio,et al. End-to-end attention-based large vocabulary speech recognition , 2015, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[12] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[13] Wei Liu,et al. SSD: Single Shot MultiBox Detector , 2015, ECCV.
[14] Wei Li,et al. DeepUNet: A Deep Fully Convolutional Network for Pixel-Level Sea-Land Segmentation , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[15] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[16] Ross B. Girshick,et al. Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[17] Peter Caccetta,et al. ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.
[18] Abhinav Gupta,et al. Non-local Neural Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[19] Xiaoming Liu,et al. Automatic segmentation of liver tumors from multiphase contrast-enhanced CT images based on FCNs , 2017, Artif. Intell. Medicine.
[20] Ross B. Girshick,et al. Mask R-CNN , 2017, 1703.06870.
[21] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[22] Zhuowen Tu,et al. Deeply-Supervised Nets , 2014, AISTATS.
[23] George Papandreou,et al. MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[24] Roberto Cipolla,et al. Semantic object classes in video: A high-definition ground truth database , 2009, Pattern Recognit. Lett..
[25] Horst Bischof,et al. Multi-label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations , 2017, STACOM@MICCAI.
[26] 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.
[27] Yongchao Gong,et al. Mask Scoring R-CNN , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Jianxiong Xiao,et al. SUN RGB-D: A RGB-D scene understanding benchmark suite , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Yi Li,et al. R-FCN: Object Detection via Region-based Fully Convolutional Networks , 2016, NIPS.
[30] Christian Igel,et al. Deep Feature Learning for Knee Cartilage Segmentation Using a Triplanar Convolutional Neural Network , 2013, MICCAI.
[31] 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).
[32] Andrea Vedaldi,et al. Deep Image Prior , 2017, International Journal of Computer Vision.
[33] Thomas Brox,et al. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation , 2016, MICCAI.
[34] Wenjun Zeng,et al. Object Detection in Videos by High Quality Object Linking , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[35] Danny Ziyi Chen,et al. Detection of Glands and Villi by Collaboration of Domain Knowledge and Deep Learning , 2015, MICCAI.
[36] Hao Chen,et al. 3D Deeply Supervised Network for Automatic Liver Segmentation from CT Volumes , 2016, MICCAI.
[37] Zhe Li,et al. Evaluate the Malignancy of Pulmonary Nodules Using the 3-D Deep Leaky Noisy-OR Network , 2017, IEEE Transactions on Neural Networks and Learning Systems.
[38] Fang Lu,et al. Automatic 3D liver location and segmentation via convolutional neural network and graph cut , 2016, International Journal of Computer Assisted Radiology and Surgery.
[39] Wei An,et al. Learning Parallax Attention for Stereo Image Super-Resolution , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Yi Yang,et al. Attention to Scale: Scale-Aware Semantic Image Segmentation , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[41] Gabriel Eilertsen,et al. HDR image reconstruction from a single exposure using deep CNNs , 2017, ACM Trans. Graph..
[42] Michael Kistler,et al. The Virtual Skeleton Database: An Open Access Repository for Biomedical Research and Collaboration , 2013, Journal of medical Internet research.
[43] Chi-Wing Fu,et al. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes , 2018, IEEE Transactions on Medical Imaging.