mlsanityData to 7 Oct 2026

The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI

arXiv 2405.18368 ↗First posted 28 May 2024cs.CVcited by 65

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Abstract (arXiv)

Gliomas are the most common malignant primary brain tumors in adults and one of the deadliest types of cancer. There are many challenges in treatment and monitoring due to the genetic diversity and high intrinsic heterogeneity in appearance, shape, histology, and treatment response. Treatments include surgery, radiation, and systemic therapies, with magnetic resonance imaging (MRI) playing a key role in treatment planning and post-treatment longitudinal assessment. The 2024 Brain Tumor Segmentation (BraTS) challenge on post-treatment glioma MRI will provide a community standard and benchmark for state-of-the-art automated segmentation models based on the largest expert-annotated post-treatment glioma MRI dataset. Challenge competitors will develop automated segmentation models to predict four distinct tumor sub-regions consisting of enhancing tissue (ET), surrounding non-enhancing T2/fluid-attenuated inversion recovery (FLAIR) hyperintensity (SNFH), non-enhancing tumor core (NETC), and resection cavity (RC). Models will be evaluated on separate validation and test datasets using standardized performance metrics utilized across the BraTS 2024 cluster of challenges, including lesion-wise Dice Similarity Coefficient and Hausdorff Distance. Models developed during this challenge will advance the field of automated MRI segmentation and contribute to their integration into clinical practice, ultimately enhancing patient care.

Key facts. Cited by 65 papers in the map (data through 7 Oct 2026). Builds on 10 of its 39 references that are in the map. First posted on arXiv 28 May 2024.

Builds on

10 of 39 references.

References · 10

  1. 2018Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challengecited by 508
  2. 2021The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classificationcited by 507
  3. 2019Automated brain extraction of multi-sequence MRI using artificial neural networkscited by 133
  4. 2023The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningiomacited by 51
  5. 2023The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)cited by 51
  6. 2023The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)cited by 49
  7. 2023The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRIcited by 35
  8. 2024Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challengecited by 14
  9. 2023The Rio Hortega University Hospital Glioblastoma dataset: a comprehensive collection of preoperative, early postoperative and recurrence MRI scans (RHUH-GBM)cited by 11
  10. 2022Automated head and neck tumor segmentation from 3D PET/CTcited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 9; 2025: 29; 2026: 27.

65 papers.

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  1. 2025Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoningcited by 217
  2. 2024MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicinecited by 79
  3. 2025BRISC: Annotated Dataset for Brain Tumor Segmentation and Classificationcited by 14
  4. 2024Multimodal Data Integration for Precision Oncology: Challenges and Future Directionscited by 10
  5. 2025A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learningcited by 7
  6. 2025Visual Instruction Pretraining for Domain-Specific Foundation Modelscited by 7
  7. 2024Adult Glioma Segmentation in Sub-Saharan Africa using Transfer Learning on Stratified Finetuning Datacited by 6
  8. 2024MIST: A Simple and Scalable End-To-End 3D Medical Imaging Segmentation Frameworkcited by 5
  9. 2024An Ensemble Approach for Brain Tumor Segmentation and Synthesiscited by 5
  10. 2024XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decodercited by 5
  11. 2025VAEVQ: Enhancing Discrete Visual Tokenization through Variational Modelingcited by 5
  12. 2025A Large Scale Benchmark for Test Time Adaptation Methods in Medical Image Segmentationcited by 5
38 more
  1. 2024Improved Multi-Task Brain Tumour Segmentation with Synthetic Data Augmentationcited by 4
  2. 2025No Modality Left Behind: Adapting to Missing Modalities via Knowledge Distillation for Brain Tumor Segmentationcited by 4
  3. 2026Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysiscited by 4
  4. 2026BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learningcited by 4
  5. 2025Fair Foundation Models for Medical Image Analysis: Challenges and Perspectivescited by 3
  6. 2024Effective Segmentation of Post-Treatment Gliomas Using Simple Approaches: Artificial Sequence Generation and Ensemble Modelscited by 2
  7. 2025Predicting brain tumour enhancement from non-contrast MR imaging with artificial intelligence: a multi-cohort retrospective diagnostic accuracy studycited by 2
  8. 2025PREDICT-GBM: A multi-center platform to advance personalized glioblastoma radiotherapy planningcited by 2
  9. 2025The Missing Piece: A Case for Pre-Training in 3D Medical Object Detectioncited by 2
  10. 2025Multimodal LLM With Hierarchical Mixture-of-Experts for VQA on 3D Brain MRIcited by 2
  11. 2025The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learningcited by 2
  12. 2026Contrast-X: A Multi-Modal Contrast Image Synthesis Benchmark and Universal Modality Flow Matchingcited by 2
  13. 2024UKAN-EP: Enhancing U-KAN with Efficient Attention and Pyramid Aggregation for 3D Multi-Modal MRI Brain Tumor Segmentationcited by 1
  14. 2025Multi-encoder nnU-Net outperforms transformer models with self-supervised pretrainingcited by 1
  15. 2025BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysiscited by 1
  16. 2025Improving Pre-trained Adult Glioma Segmentation Models Using only Post-processing Techniquescited by 1
  17. 2026BTReport: A Framework for Brain Tumor Radiology Report Generation with Clinically Relevant Featurescited by 1
  18. 2026VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignmentcited by 1
  19. 2025Real-Time Brain Tumor Detection in Intraoperative Ultrasound Using YOLO11: From Model Training to Deployment in the Operating Roomcited by 0
  20. 2025Full-Head Segmentation of MRI with Abnormal Brain Anatomy: Model and Data Releasecited by 0
  21. 2025Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methodscited by 0
  22. 2025Pre- and Post-Treatment Glioma Segmentation with the Medical Imaging Segmentation Toolkitcited by 0
  23. 2025Automatic and standardized surgical reporting for central nervous system tumorscited by 0
  24. 2025NeuroRAD-FM: A Foundation Model for Neuro-Oncology with Distributionally Robust Trainingcited by 0
  25. 2025On-the-Fly Data Augmentation for Brain Tumor Segmentationcited by 0
  26. 2025Synergistic Modality-and-Slice Memory Framework for Cross-Modal 3D Brain Tumor Segmentationcited by 0
  27. 2025A Structured Review and Quantitative Profiling of Public Brain MRI Datasets for Foundation Model Developmentcited by 0
  28. 2025MedVision: Benchmarking Quantitative Medical Image Analysiscited by 0
  29. 2025Clinical Interpretability of Deep Learning Segmentation Through Shapley-Derived Agreement and Uncertainty Metricscited by 0
  30. 2025A unified FLAIR hyperintensity segmentation model for various CNS tumor types and acquisition time pointscited by 0
  31. 2025Bidirectional human-AI collaboration in brain tumour assessments improves both expert human and AI agent performancecited by 0
  32. 2026Variance-Penalized MC-Dropout as a Learned Smoothing Prior for Brain Tumour Segmentationcited by 0
  33. 2026MieDB-100k: A Comprehensive Dataset for Medical Image Editingcited by 0
  34. 2026MeDUET: Disentangled Unified Pretraining for 3D Medical Image Synthesis and Analysiscited by 0
  35. 2026Tell2Adapt: A Unified Framework for Source Free Unsupervised Domain Adaptation via Vision Foundation Modelcited by 0
  36. 2026ADP-FL-MedSeg: Adaptive Differential Privacy for Federated Medical Segmentation Across Diverse Modalitiescited by 0
  37. 2026Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysiscited by 0
  38. 2026SegWithU: Uncertainty as Perturbation Energy for Single-Forward-Pass Risk-Aware Medical Image Segmentationcited by 0

50 most cited of 65 All 65 (JSON)