mlsanityData to 7 Oct 2026

SS-3DCapsNet: Self-supervised 3D Capsule Networks for Medical Segmentation on Less Labeled Data

arXiv 2201.05905 ↗First posted 15 Jan 2022eess.IV cs.CVcited by 10

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Abstract (arXiv)

Capsule network is a recent new deep network architecture that has been applied successfully for medical image segmentation tasks. This work extends capsule networks for volumetric medical image segmentation with self-supervised learning. To improve on the problem of weight initialization compared to previous capsule networks, we leverage self-supervised learning for capsule networks pre-training, where our pretext-task is optimized by self-reconstruction. Our capsule network, SS-3DCapsNet, has a UNet-based architecture with a 3D Capsule encoder and 3D CNNs decoder. Our experiments on multiple datasets including iSeg-2017, Hippocampus, and Cardiac demonstrate that our 3D capsule network with self-supervised pre-training considerably outperforms previous capsule networks and 3D-UNets.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 32 of its 50 references that are in the map. First posted on arXiv 15 Jan 2022.

Builds on

32 of 50 references.

References · 32

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  3. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 6,979
  4. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
  5. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
  6. 2014Conditional Generative Adversarial Netscited by 2,152
  7. 20163D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotationcited by 1,471
  8. 2016Colorful Image Colorizationcited by 1,113
  9. 2017Dynamic Routing Between Capsulescited by 689
  10. 2019The Liver Tumor Segmentation Benchmark (LiTS)cited by 504
  11. 2015Unsupervised Learning of Video Representations using LSTMscited by 434
  12. 2019A large annotated medical image dataset for the development and evaluation of segmentation algorithmscited by 371
20 more
  1. 2019Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentationcited by 258
  2. 2018Cooperative Learning of Audio and Video Models from Self-Supervised Synchronizationcited by 246
  3. 2020U-Net and its variants for medical image segmentation: theory and applicationscited by 169
  4. 2020Medical Image Segmentation Using Deep Learning: A Surveycited by 163
  5. 2016Learning Features by Watching Objects Movecited by 138
  6. 2016The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentationcited by 122
  7. 2019Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentationcited by 121
  8. 2017DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentationcited by 110
  9. 2018Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognitioncited by 40
  10. 2020Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Datacited by 38
  11. 2018Cross and Learn: Cross-Modal Self-Supervisioncited by 34
  12. 2021Deep reinforcement learning in medical imaging: A literature reviewcited by 34
  13. 2018Capsules for Object Segmentationcited by 30
  14. 2020Capsules for Biomedical Image Segmentationcited by 18
  15. 2020Offset Curves Loss for Imbalanced Problem in Medical Segmentationcited by 11
  16. 2020A Multi-task Contextual Atrous Residual Network for Brain Tumor Detection & Segmentationcited by 9
  17. 2018Dilated Convolutions in Neural Networks for Left Atrial Segmentation in 3D Gadolinium Enhanced-MRIcited by 6
  18. 2018Deep Recurrent Level Set for Segmenting Brain Tumorscited by 6
  19. 2021DAM-AL: Dilated Attention Mechanism with Attention Loss for 3D Infant Brain Image Segmentationcited by 6
  20. 2020Flow-based Deformation Guidance for Unpaired Multi-Contrast MRI Image-to-Image Translationcited by 4

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Cited by year

Citing papers per year: 2022: 4; 2023: 2; 2024: 3; 2025: 1.

10 papers.

  1. 2023MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentationcited by 28
  2. 2022EmbryosFormer: Deformable Transformer and Collaborative Encoding-Decoding for Embryos Stage Development Classificationcited by 12
  3. 2024DynaSeg: A Deep Dynamic Fusion Method for Unsupervised Image Segmentation Incorporating Feature Similarity and Spatial Continuitycited by 4
  4. 20223DConvCaps: 3DUnet with Convolutional Capsule Encoder for Medical Image Segmentationcited by 3
  5. 2022Multimodality Multi-Lead ECG Arrhythmia Classification using Self-Supervised Learningcited by 3
  6. 2023A Survey of the Impact of Self-Supervised Pretraining for Diagnostic Tasks with Radiological Imagescited by 2
  7. 2024CarcassFormer: An End-to-end Transformer-based Framework for Simultaneous Localization, Segmentation and Classification of Poultry Carcass Defectcited by 1
  8. 2022CapsNet for Medical Image Segmentationcited by 0
  9. 20243D-EffiViTCaps: 3D Efficient Vision Transformer with Capsule for Medical Image Segmentationcited by 0
  10. 2025The Convergence of Dynamic Routing between Capsulescited by 0