mlsanityData to 7 Oct 2026

Prototype Knowledge Distillation for Medical Segmentation with Missing Modality

arXiv 2303.09830 ↗First posted 17 Mar 2023cs.CVcited by 24

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Abstract (arXiv)

Multi-modality medical imaging is crucial in clinical treatment as it can provide complementary information for medical image segmentation. However, collecting multi-modal data in clinical is difficult due to the limitation of the scan time and other clinical situations. As such, it is clinically meaningful to develop an image segmentation paradigm to handle this missing modality problem. In this paper, we propose a prototype knowledge distillation (ProtoKD) method to tackle the challenging problem, especially for the toughest scenario when only single modal data can be accessed. Specifically, our ProtoKD can not only distillate the pixel-wise knowledge of multi-modality data to single-modality data but also transfer intra-class and inter-class feature variations, such that the student model could learn more robust feature representation from the teacher model and inference with only one single modality data. Our method achieves state-of-the-art performance on BraTS benchmark. The code is available at urlhttps://github.com/SakurajimaMaiii/ProtoKD.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). Builds on 14 of its 18 references that are in the map. First posted on arXiv 17 Mar 2023.

Builds on

14 of 18 references.

References · 14

  1. 2015Distilling the Knowledge in a Neural Networkcited by 10,076
  2. 2017Prototypical Networks for Few-shot Learningcited by 3,001
  3. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
  4. 2014FitNets: Hints for Thin Deep Netscited by 1,619
  5. 2015Unifying distillation and privileged informationcited by 218
  6. 2022mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentationcited by 94
  7. 2019Hetero-Modal Variational Encoder-Decoder for Joint Modality Completion and Segmentationcited by 68
  8. 2021Knowledge distillation from multi-modal to mono-modal segmentation networkscited by 68
  9. 2020Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusioncited by 67
  10. 2022GAMMA Challenge:Glaucoma grAding from Multi-Modality imAgescited by 45
  11. 2021Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalitiescited by 42
  12. 2019CollaGAN : Collaborative GAN for Missing Image Data Imputationcited by 33
2 more
  1. 2020Multi-Domain Image Completion for Random Missing Input Datacited by 30
  2. 2022Rethinking Alignment and Uniformity in Unsupervised Semantic Segmentationcited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 12; 2025: 6; 2026: 3.

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  1. 2024Deep Multimodal Learning with Missing Modality: A Surveycited by 89
  2. 2024Bootstrapping Chest CT Image Understanding by Distilling Knowledge from X-ray Expert Modelscited by 24
  3. 2024Cross-Modal Prototype based Multimodal Federated Learning under Severely Missing Modalitycited by 21
  4. 2024PASSION: Towards Effective Incomplete Multi-Modal Medical Image Segmentation with Imbalanced Missing Ratescited by 17
  5. 2024Multimodal Data Integration for Precision Oncology: Challenges and Future Directionscited by 10
  6. 2024Borrowing Treasures from Neighbors: In-Context Learning for Multimodal Learning with Missing Modalities and Data Scarcitycited by 5
  7. 2024MedMAP: Promoting Incomplete Multi-modal Brain Tumor Segmentation with Alignmentcited by 4
  8. 2025Revisiting Cross-Modal Knowledge Distillation: A Disentanglement Approach for RGBD Semantic Segmentationcited by 4
  9. 2024Towards a Universal 3D Medical Multi-modality Generalization via Learning Personalized Invariant Representationcited by 3
  10. 2023Black-box Source-free Domain Adaptation via Two-stage Knowledge Distillationcited by 2
  11. 2024Enhancing Single-Slice Segmentation with 3D-to-2D Unpaired Scan Distillationcited by 2
  12. 2025Adaptive Conformal Guidance for Learning under Uncertaintycited by 2
12 more
  1. 2023A vision transformer-based framework for knowledge transfer from multi-modal to mono-modal lymphoma subtyping modelscited by 1
  2. 2024A Multimodal Feature Distillation with Mamba-Transformer Network for Brain Tumor Segmentation with Incomplete Modalitiescited by 1
  3. 2023Semi-supervised Semantic Segmentation via Boosting Uncertainty on Unlabeled Datacited by 0
  4. 2024Complementary Information Mutual Learning for Multimodality Medical Image Segmentationcited by 0
  5. 2024Unveiling Incomplete Modality Brain Tumor Segmentation: Leveraging Masked Predicted Auto-Encoder and Divergence Learningcited by 0
  6. 2025RMMSS: Towards Advanced Robust Multi-Modal Semantic Segmentation with Hybrid Prototype Distillation and Feature Selectioncited by 0
  7. 2025From Swath to Full-Disc: Advancing Precipitation Retrieval with Multimodal Knowledge Expansioncited by 0
  8. 2025DMAF-Net: An Effective Modality Rebalancing Framework for Incomplete Multi-Modal Medical Image Segmentationcited by 0
  9. 2025Robust Brain Tumor Segmentation with Incomplete MRI Modalities Using H"older Divergence and Mutual Information-Enhanced Knowledge Transfercited by 0
  10. 2026Maximizing T2-Only Prostate Cancer Localization from Expected Diffusion Weighted Imagingcited by 0
  11. 2026Beyond Instance-Level Self-Supervision in 3D Multi-Modal Medical Imagingcited by 0
  12. 2026VeCAS: Vessel-Focused Contrast-Free Angiogram Synthesis for Vascular Interventionscited by 0