mlsanityData to 7 Oct 2026

Extending nn-UNet for brain tumor segmentation

arXiv 2112.04653 ↗First posted 9 Dec 2021eess.IV cs.CVcited by 36

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Abstract (arXiv)

Brain tumor segmentation is essential for the diagnosis and prognosis of patients with gliomas. The brain tumor segmentation challenge has continued to provide a great source of data to develop automatic algorithms to perform the task. This paper describes our contribution to the 2021 competition. We developed our methods based on nn-UNet, the winning entry of last year competition. We experimented with several modifications, including using a larger network, replacing batch normalization with group normalization, and utilizing axial attention in the decoder. Internal 5-fold cross validation as well as online evaluation from the organizers showed the effectiveness of our approach, with minor improvement in quantitative metrics when compared to the baseline. The proposed models won first place in the final ranking on unseen test data. The codes, pretrained weights, and docker image for the winning submission are publicly available at https://github.com/rixez/Brats21_KAIST_MRI_Lab

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). Builds on 16 of its 31 references that are in the map. First posted on arXiv 9 Dec 2021.

Builds on

16 of 31 references.

References · 16

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  4. 2020Language Models are Few-Shot Learnerscited by 32,199
  5. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  6. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 6,979
  7. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
  8. 2018Group Normalizationcited by 1,514
  9. 2018Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challengecited by 508
  10. 2021The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classificationcited by 507
  11. 2019Axial Attention in Multidimensional Transformerscited by 350
  12. 2020Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentationcited by 326
4 more
  1. 20183D MRI brain tumor segmentation using autoencoder regularizationcited by 324
  2. 2016Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentationcited by 263
  3. 2020nnU-Net for Brain Tumor Segmentationcited by 103
  4. 2017Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentationcited by 58

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 9; 2023: 8; 2024: 12; 2025: 4; 2026: 3.

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  1. 2022One Model to Synthesize Them All: Multi-contrast Multi-scale Transformer for Missing Data Imputationcited by 40
  2. 2024How we won BraTS 2023 Adult Glioma challenge? Just faking it! Enhanced Synthetic Data Augmentation and Model Ensemble for brain tumour segmentationcited by 27
  3. 2022CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentationcited by 24
  4. 2023Neuralizer: General Neuroimage Analysis without Re-Trainingcited by 24
  5. 20233D TransUNet: Advancing Medical Image Segmentation through Vision Transformerscited by 20
  6. 2022Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solutioncited by 17
  7. 2022Preoperative brain tumor imaging: models and software for segmentation and standardized reportingcited by 9
  8. 2023The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Datasetcited by 9
  9. 2022High-Resolution Swin Transformer for Automatic Medical Image Segmentationcited by 8
  10. 2022Large-Kernel Attention for 3D Medical Image Segmentationcited by 7
  11. 2022Voxels Intersecting along Orthogonal Levels Attention U-Net for Intracerebral Haemorrhage Segmentation in Head CTcited by 4
  12. 2022Hybrid Window Attention Based Transformer Architecture for Brain Tumor Segmentationcited by 4
24 more
  1. 2024Improved Multi-Task Brain Tumour Segmentation with Synthetic Data Augmentationcited by 4
  2. 2023Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networkscited by 3
  3. 2024Interactive Image Selection and Training for Brain Tumor Segmentation Networkcited by 3
  4. 2024Unsupervised Domain Adaptation for Pediatric Brain Tumor Segmentationcited by 3
  5. 2024T1-contrast Enhanced MRI Generation from Multi-parametric MRI for Glioma Patients with Latent Tumor Conditioningcited by 3
  6. 2023Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentationcited by 2
  7. 2023Brain MRI Screening Tool with Federated Learningcited by 2
  8. 2024Multi-modal MRI Translation via Evidential Regression and Distribution Calibrationcited by 2
  9. 2024Transferring Knowledge from High-Quality to Low-Quality MRI for Adult Glioma Diagnosiscited by 2
  10. 2022CANet: Channel Extending and Axial Attention Catching Network for Multi-structure Kidney Segmentationcited by 1
  11. 2024Train-Free Segmentation in MRI with Cubical Persistent Homologycited by 1
  12. 2024Segmentation of Pediatric Brain Tumors using a Radiologically informed, Deep Learning Cascadecited by 1
  13. 2023Ensemble Learning with Residual Transformer for Brain Tumor Segmentationcited by 0
  14. 2023Glioblastoma Tumor Segmentation using an Ensemble of Vision Transformerscited by 0
  15. 2024Self-calibrated convolution towards glioma segmentationcited by 0
  16. 2024Re-DiffiNet: Modeling discrepancies in tumor segmentation using diffusion modelscited by 0
  17. 2024GASA-UNet: Global Axial Self-Attention U-Net for 3D Medical Image Segmentationcited by 0
  18. 2025Efficient 3D Brain Tumor Segmentation with Axial-Coronal-Sagittal Embeddingcited by 0
  19. 2025AI-Driven MRI-based Brain Tumour Segmentation Benchmarkingcited by 0
  20. 2025How We Won BraTS-SSA 2025: Brain Tumor Segmentation in the Sub-Saharan African Population Using Segmentation-Aware Data Augmentation and Model Ensemblingcited by 0
  21. 2025TwinSegNet: A Digital Twin-Enabled Federated Learning Framework for Brain Tumor Analysiscited by 0
  22. 2026Fairboard: a quantitative framework for equity assessment of healthcare modelscited by 0
  23. 2026Prob-BBDM: a Probabilistic Brownian Bridge Diffusion Model for MRI sequence image-to-image translationcited by 0
  24. 2026Reliability analysis for BraTS-GoAT segmentation: a controlled robustness study of deep-ensemble uncertaintycited by 0