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Mpaf-Net: Medical Image Segmentation Based on Multi-Scale Attention Fusion Convolutional Neural Network

https://doi.org/10.2139/ssrn.4689418
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UNet++: A Nested U-Net Architecture for Medical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_1openalex-extracted
CBAM: Convolutional Block Attention Module
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_49openalex-extracted
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-030-59719-1_77openalex-extracted
SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-030-59725-2_26openalex-extracted
PraNet: Parallel Reverse Attention Network for Polyp Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-extracted
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-46976-8_19openalex-extracted
The Importance of Skip Connections in Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/s10278-019-00227-xopenalex-extracted
Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges
inferredcites →https://doi.org/10.1007/s12065-020-00540-3openalex-extracted
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A survey on U-shaped networks in medical image segmentations
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MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation
inferredcites →https://doi.org/10.1038/s41592-019-0612-7openalex-extracted
Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl
inferredcites →https://doi.org/10.1049/ipr2.12346openalex-extracted
PCAF‐Net: A liver segmentation network based on deep learning
inferredcites →https://doi.org/10.1109/5.726791openalex-extracted
Gradient-based learning applied to document recognition
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Cell-Net: Embryonic Cell Counting and Centroid Localization via Residual Incremental Atrous Pyramid and Progressive Upsampling Convolution
inferredcites →https://doi.org/10.1109/bibe50027.2020.00099openalex-extracted
Exploiting the Transferability of Deep Learning Systems Across Multi-modal Retinal Scans for Extracting Retinopathy Lesions
inferredcites →https://doi.org/10.1109/cbms49503.2020.00111openalex-extracted
DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2017.106openalex-extracted
Feature Pyramid Networks for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.660openalex-extracted
Pyramid Scene Parsing Network
inferredcites →https://doi.org/10.1109/cvpr.2019.00326openalex-extracted
Dual Attention Network for Scene Segmentation
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01155openalex-extracted
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01350openalex-extracted
Coordinate Attention for Efficient Mobile Network Design
inferredcites →https://doi.org/10.1109/icassp40776.2020.9053405openalex-extracted
UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation
inferredcites →https://doi.org/10.1109/iccv.2019.00533openalex-extracted
Gated-SCNN: Gated Shape CNNs for Semantic Segmentation
inferredcites →https://doi.org/10.1109/isbi.2019.8759477openalex-extracted
Focusnet: An Attention-Based Fully Convolutional Network for Medical Image Segmentation
inferredcites →https://doi.org/10.1109/isbi.2019.8759555openalex-extracted
Feature Fusion Encoder Decoder Network for Automatic Liver Lesion Segmentation
inferredcites →https://doi.org/10.1109/ism46123.2019.00049openalex-extracted
ResUNet++: An Advanced Architecture for Medical Image Segmentation
inferredcites →https://doi.org/10.1109/jbhi.2019.2895803openalex-extracted
Dermoscopy Image Analysis: Overview and Future Directions
inferredcites →https://doi.org/10.1109/lgrs.2018.2802944openalex-extracted
Road Extraction by Deep Residual U-Net
inferredcites →https://doi.org/10.1109/tmi.2019.2959609openalex-extracted
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
inferredcites →https://doi.org/10.1109/tpami.2015.2389824openalex-extracted
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
inferredcites →https://doi.org/10.1109/tpami.2017.2699184openalex-extracted
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
inferredcites →https://doi.org/10.1109/tpami.2021.3059968openalex-extracted
Image Segmentation Using Deep Learning: A Survey
inferredcites →https://doi.org/10.24963/ijcai.2022/135openalex-extracted
ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation
inferredcites →https://doi.org/10.48550/arxiv.1409.0473openalex-extracted
Neural Machine Translation by Jointly Learning to Align and Translate
inferredcites →https://doi.org/10.48550/arxiv.1411.4038openalex-extracted
Fully Convolutional Networks for Semantic Segmentation
inferredcites →https://doi.org/10.48550/arxiv.1412.7755openalex-extracted
Multiple Object Recognition with Visual Attention
inferredcites →https://doi.org/10.48550/arxiv.1709.01507openalex-extracted
Squeeze-and-Excitation Networks
inferredcites →https://doi.org/10.48550/arxiv.1804.03999openalex-extracted
Attention U-Net: Learning Where to Look for the Pancreas
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Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition
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