BraTS2021

Description from the archive archive 2025-07-28.

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Most implemented papers archive 2025-07-28

10 shown of 10 papers with code (15 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI
  30 Aug 2023 3 repositories listed
  Furthermore, we combine image translation with a masked conditional diffusion model, which attempts to `imagine' what tissue exists under a masked area, further exposing unknown patterns as the generative model fails to…
• UPMAD-Net: A Brain Tumor Segmentation Network with Uncertainty Guidance and Adaptive Multimodal Feature Fusion
  6 May 2025 1 repository listed
  By incorporating the prior knowledge and employing the uncertainty estimation method, the robustness and performance were improved.
• Promptable Counterfactual Diffusion Model for Unified Brain Tumor Segmentation and Generation with MRIs
  17 Jul 2024 1 repository listed
  We introduce a novel promptable counterfactual diffusion model as a unified solution for brain tumor segmentation and generation in MRI.
• LoRA-PT: Low-Rank Adapting UNETR for Hippocampus Segmentation Using Principal Tensor Singular Values and Vectors
  16 Jul 2024 1 repository listed
  This method transfers the pre-trained UNETR model on the BraTS2021 dataset to the hippocampus segmentation task.
• Non-Adversarial Learning: Vector-Quantized Common Latent Space for Multi-Sequence MRI
  3 Jul 2024 1 repository listed
  We propose a generative model that compresses discrete representations of each sequence to estimate the Gaussian distribution of vector-quantized common (VQC) latent space between multiple sequences.
• GLIMS: Attention-Guided Lightweight Multi-Scale Hybrid Network for Volumetric Semantic Segmentation
  27 Apr 2024 1 repository listed
  Notably, GLIMS achieved this high performance with a significantly reduced number of trainable parameters.
• An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis
  3 Jul 2023 1 repository listed
  Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons.
• Efficient Subclass Segmentation in Medical Images
  1 Jul 2023 1 repository listed
  One feasible way to reduce the cost is to annotate with coarse-grained superclass labels while using limited fine-grained annotations as a complement.
• BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor Segmentation
  25 Sep 2021 1 repository listed
  Convolutional neural networks (CNNs) have achieved remarkable success in automatically segmenting organs or lesions on 3D medical images.
• Automatic Brain Tumor Segmentation with Scale Attention Network
  6 Nov 2020 1 repository listed
  Automatic segmentation of brain tumors is an essential but challenging step for extracting quantitative imaging biomarkers for accurate tumor detection, diagnosis, prognosis, treatment planning and assessment.