【论文解读】语义分割&医学图像分割论文合集_cs-net: channel and spatial attention network for

description: 整理自己看过和待看的一些主要关于图像分割包括其他领域的论文，不定时更新…

综述篇

• Deep learning for cardiac image segmentation: A review [2019]
• Deep Semantic Segmentation of Natural and Medical Images: A Review [2019]
• Understanding Deep Learning Techniques for Image Segmentation [2019]
• Machine Learning Techniques for Biomedical Image Segmentation: An Overview of Technical Aspects and Introduction to State-of-Art Applications [2019]
• Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation [2019]
• Deep Learning for Image Super-resolution: A Survey [2019] [超分辨率]

开篇之作

• Fully convolutional networks for semantic segmentation [2015] [CVPR] [FCN] [全卷积]

编码-解码结构

• Learning Deconvolution Network for Semantic Segmentation
• SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
• U-Net: Convolutional Networks for Biomedical Image Segmentation [2015] [MICCAI] [UNet]
• UNet++: A Nested U-Net Architecture for Medical Image Segmentation [2018] [DLMIA]
• UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation [2019] [IEEE TMI]
• V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation [2016] [3DV]
• The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
• Stacked Deconvolutional Network for Semantic Segmentation
• RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
• Large Kernel Matters – Improve Semantic Segmentation by Global Convolutional Network
• Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes
• 3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes
• Rethinking Atrous Convolution for Semantic Image Segmentation [2017] [DeepLabV3]
• Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation [2018] [ECCV] [DeepLabV3+]
• Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation
• CE-Net: Context Encoder Network for 2D Medical Image Segmentation [2019] [TMI]
• Towards semi-supervised segmentation via image-to-image translation [ 2019]
• Automatic Lesion Boundary Segmentation in Dermoscopic Images with Ensemble Deep Learning Methods [2019]
• Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation [2019] [CVPR] [DUpsample]
• ExFuse: Enhancing Feature Fusion for Semantic Segmentation [2018] [ECCV] [ExFuse] [增强特征融合]
• Gated-SCNN: Gated Shape CNNs for Semantic Segmentation [2019] [ICCV] [two stream] [边缘提取]

多尺度上下文融合

• Pyramid Scene Parsing Network [2017] [CVPR] [PSPNet]
• (DeepLab V3) Rethinking Atrous Convolution for Semantic Image Segmentation
• (DeepLab V3+) Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
• (GCN) Large Kernel Matters – Improve Semantic Segmentation by Global Convolutional Network [2017] [CVPR] [大内核]
• Context Encoding for Semantic Segmentation
• (EncNet) Context contrasted feature and gated multiscale aggregation for scene segmentation [2018] [CVPR] [注意力机制]
• RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation [2017] [CVPR]

注意力机制

• Squeeze-and-Excitation Networks [2018] [CVPR] [SENet]
• Pyramid Feature Attention Network for Saliency detection [2019] [CVPR] [双重注意力] [边缘保护损失] [显著性检测]
• Residual Attention Network for Image Classification
• Dual Attention Network for Scene Segmentation [ 2019] [CVPR] [DANet] [场景分割] [双重注意力]
• CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation [2019] [MICCAI] [视网膜] [双重注意力]
• Pyramid Attention Network for Semantic Segmentation [2018][PAN]
• Attention to Scale: Scale-aware Semantic Image Segmentation
• ASDNet: Attention based semi-supervised deep networks for medical image segmentation
• Multi-scale self-guided attention for medical image segmentation [ 2019 ]
• Autofocus Layer for Semantic Segmentation
• Attention guided U-Net for accurate iris segmentation
• nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation
• Attention dense-U-Net for automatic breast mass segmentation in digital mammogram
• RASNet: Segmentation for Tracking Surgical Instruments in Surgical Videos Using Refined Attention Segmentation Network [ 2019 ]
• Attention U-Net: Learning Where to Look for the Pancreas
• Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

对抗网络

• Generative Adversarial Networks
• Generative Adversarial Network in Medical Imaging: A Review
• Semantic Segmentation using Adversarial Networks
• Synthesizing Filamentary Structured Images with GANs
• Towards Adversarial Retinal Image Synthesis
• Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks
• PAN: Projective Adversarial Network for Medical Image Segmentation [2019]
• SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation
• SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays
• Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection
• Adversarial training and dilated convolutions for brain MRI segmentation
• Generative adversarial network based synthesis for supervised medical image segmentation
• A conditional adversarial network for semantic segmentation of brain tumor
• Automatic Liver Segmentation Using an Adversarial Image-to-Image Network
• Deep adversarial networks for biomedical image segmentation utilizing unannotated images
• A Refined Equilibrium Generative Adversarial Network for Retinal Vessel Segmentation

模型压缩

• NAS-Unet: Neural architecture search for medical image segmentation
• A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation [2019]
• Efficient segmentation of medical images using dilated residual networks
• Spinal cord gray matter segmentation using deep dilated convolutions
• Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks [2019]
• Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation

降低计算复杂度

• MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
• IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification
• Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications (tensor factoriaztion 张量分解)
• V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation (pruning 剪枝)
• EIE: Efficient Inference Engine on Compressed Deep Neural Network (稀疏连接)
• Convolutional Neural Fabrics (神经结构搜索)
• Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation [2019]
• Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

递归神经网络 RNN

• Recurrent neural networks for aortic image sequence segmentation with sparse annotations
• Fully convolutional structured LSTM networks for joint 4D medical image segmentation
• MDS-Net: A Model-Driven Stack-Based Fully Convolutional Network for Pancreas Segmentation [2019]
• Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
• Race-net: a recurrent neural network for biomedical image segmentation
• Fine-grained Recurrent Neural Networks for Automatic Prostate Segmentation in Ultrasound Images
• Retinal image classification via vasculature-guided sequential attention
• Tree-LSTM: Using LSTM to Encode Memory in Anatomical Tree Prediction from 3D Images

基于图像合成 Image Synthesis 数据增强

• Adversarial image synthesis for unpaired multi-modal cardiac data
• Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network
• Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth
• Mask2Lesion: Mask-Constrained Adversarial Skin Lesion Image Synthesis
• Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation
• Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks
• MRI Cross-Modality NeuroImage-to-NeuroImage Translation
• 3D cGAN based cross-modality MR image synthesis for brain tumor segmentation
• Learning More with Less: GAN-based Medical Image Augmentation [2019]

弱监督 Weakly Supervised

• Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation
• FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference [2019]
• Constrained-CNN losses for weakly supervised segmentation
• Weakly supervised fully convolutional network for PET lesion segmentation
• Learning to Segment Skin Lesions from Noisy Annotations [2019]
• InfoMask: Masked Variational Latent Representation to Localize Chest Disease [2019]
• Discretely-constrained deep network for weakly supervised segmentation [2019]
• Deep semi-supervised segmentation with weight-averaged consistency targets
• Unsupervised domain adaptation for medical imaging segmentation with self-ensembling

多任务 Multitask

• Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks
• Multitask convolutional neural network for patient detection and skin segmentation in continuous non
• Multi-task learning for the segmentation of thoracic organs at risk in CT images
• A multi-task U-net for segmentation with lazy labels [2019]
• Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos [ 2019 ]
• Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images
• Multitask Classification and Segmentation for Cancer Diagnosis in Mammography [2019]
• Usiigaci: Instance-aware cell tracking in stain-free phase contrast microscopy enabled by machine learning
• Adapting Mask-RCNN for Automatic Nucleus Segmentation
• Mask-RCNN and U-net Ensembled for Nuclei Segmentation [2019]
• Multi-path dilated residual network for nuclei segmentation and detection
• Computational staining of pathology images to study tumor microenvironment in lung cancer
• Utilizing Mask R-CNN for detection and segmentation of oral diseases
• Instance-based segmentation for boundary detection of neuropathic ulcers through Mask-RCNN
• Sequential Rib Labeling and Segmentation in Chest X-Ray using Mask R-CNN [2019]
• Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection
• Lung Nodules Detection and Segmentation Using 3D Mask-RCNN [2019]

轻量级神经网络

• MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications [2017] [CVPR] [MobileNet]
• ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices [2018] [CVPR] [ShuffleNet]
• MobileNetV2: Inverted Residuals and Linear Bottlenecks [2018] [CVPR] [MobileNetV2]
• ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design [2018] [ECCV] [ShuffleNetV2]
• Searching for MobileNetV3 [2019] [ICCV] [NAS]
• MnasNet: Platform-Aware Neural Architecture Search for Mobile [2019] [CVPR] [NAS]
• GhostNet: More Features from Cheap Operations [2020] [CVPR]

超分辨率

• Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network [2016] [CVPR] [PixelShuffle]

前列腺分割 Prostate Segmentation

• Boundary-weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation [2019] [TMI] [迁移学习] [领域自适应] [边界损失]
• MS-Net：Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Data [2020] [TMI] [知识迁移] [多站点学习]

显著性检测

• Pyramid Feature Attention Network for Saliency detection [2019] [CVPR] [双重注意力] [边缘保护损失] [显著性检测]