UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation
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- Type
- article
- Published
- 2020-04-19
- Cited by
- 2,784
- References
- 13
- Access
- Open access
- OpenAlex
- https://openalex.org/W3015788359
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:215828394
Keywords
Computer science, Segmentation, Artificial intelligence, Feature (linguistics), Image segmentation
References
- Multiscale structural similarity for image quality assessment
- Fully convolutional networks for semantic segmentation
- A Tutorial on the Cross-Entropy Method
- DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
- Pyramid Scene Parsing Network
- Rethinking Atrous Convolution for Semantic Image Segmentation
- Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
- DeepRoadMapper: Extracting Road Topology from Aerial Images
- Attention U-Net: Learning Where to Look for the Pancreas
- UNet++: A Nested U-Net Architecture for Medical Image Segmentation
- U-Net: Convolutional Networks for Biomedical Image Segmentation
- Focal Loss for Dense Object Detection
- Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Cited by
- CAggNet: Crossing Aggregation Network for Medical Image Segmentation
- MACU-Net Semantic Segmentation from High-Resolution Remote Sensing Images
- Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation
- Brain stroke lesion segmentation using consistent perception generative adversarial network
- Multi-Attention-Network for Semantic Segmentation of High-Resolution Remote Sensing Images
- BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation in Patients With Cerebrovascular Disease
- SCOAT-Net: A novel network for segmenting COVID-19 lung opacification from CT images
- Point-Sampling Method Based on 3D U-Net Architecture to Reduce the Influence of False Positive and Solve Boundary Blur Problem in 3D CT Image Segmentation
- KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation
- Adaptive Neural Layer for Globally Filtered Segmentation
- Covariance Self-Attention Dual Path UNet for Rectal Tumor Segmentation
- Multiattention Network for Semantic Segmentation of Fine-Resolution Remote Sensing Images
- Adaptive Neural Layer for Global Filtering in Computer Vision.
- IPN-V2 and OCTA-500: Methodology and Dataset for Retinal Image Segmentation
- Development of an Interactive Semantic Medical Image Segmentation System
- A Lightweight Deep Network for 3D Medical Image Segmentation
- A Multiple Layer U-Net, Un-Net, for Liver and Liver Tumor Segmentation in CT
- TMD-Unet: Triple-Unet with Multi-Scale Input Features and Dense Skip Connection for Medical Image Segmentation
- TU-Net: A Precise Network for Tongue Segmentation
- Subsurface Pipes Detection Using DNN-based Back Projection on GPR Data
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