Volumetric Medical Image Segmentation

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

29 shown of 29 papers with code (58 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.

• V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
  15 Jun 2016 28 repositories listed Syntology ran 2 of 22 samples · 20 unverified
  Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields.
• On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task
  6 Jul 2017 4 repositories listed
  To illustrate its efficiency of learning 3D representation from large-scale image data, the proposed network is validated with the challenging task of parcellating 155 neuroanatomical structures from brain MR images.
• Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation
  14 Jul 2023 2 repositories listed
  While recent advances in deep learning have improved the performance of volumetric medical image segmentation models, these models cannot be deployed for real-world applications immediately due to their vulnerability to…
• nnFormer: Interleaved Transformer for Volumetric Segmentation
  7 Sep 2021 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Transformer, the model of choice for natural language processing, has drawn scant attention from the medical imaging community.
• Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation
  19 Jul 2018 2 repositories listed Syntology ran 2 of 3 samples · 1 unverified
  In this paper, we test whether this algorithm, which was shown to improve semantic segmentation for 2D RGB images, is able to improve segmentation quality for 3D multi-modal medical images.
• TextBraTS: Text-Guided Volumetric Brain Tumor Segmentation with Innovative Dataset Development and Fusion Module Exploration
  20 Jun 2025 1 repository listed
  Deep learning has demonstrated remarkable success in medical image segmentation and computer-aided diagnosis.
• SWDL: Stratum-Wise Difference Learning with Deep Laplacian Pyramid for Semi-Supervised 3D Intracranial Hemorrhage Segmentation
  12 Jun 2025 1 repository listed
  Unlike conventional SSL methods that primarily focus on high-confidence pseudo-labels or consistency regularization, we propose SWDL-Net, a novel SSL framework that exploits the complementary advantages of Laplacian…
• Memorizing SAM: 3D Medical Segment Anything Model with Memorizing Transformer
  18 Dec 2024 1 repository listed
  In this work, we investigate whether introducing the memory mechanism as a plug-in, specifically the ability to memorize and recall internal representations of past inputs, can improve the performance of SAM with…
• Improving 3D Medical Image Segmentation at Boundary Regions using Local Self-attention and Global Volume Mixing
  20 Oct 2024 1 repository listed
  In this work, we propose a novel hierarchical encoder-decoder-based framework that strives to explicitly capture the local and global dependencies for volumetric 3D medical image segmentation.
• FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty Quantification
  17 Jul 2024 1 repository listed
  Accurate segmentation of anatomical structures and pathological regions in medical images is crucial for diagnosis, treatment planning, and disease monitoring.
• LHU-Net: A Light Hybrid U-Net for Cost-Efficient, High-Performance Volumetric Medical Image Segmentation
  7 Apr 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  The rise of Transformer architectures has revolutionized medical image segmentation, leading to hybrid models that combine Convolutional Neural Networks (CNNs) and Transformers for enhanced accuracy.
• D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image Segmentation
  15 Mar 2024 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  D-Net is able to effectively utilize a multi-scale large receptive field and adaptively harness global contextual information.
• SegVol: Universal and Interactive Volumetric Medical Image Segmentation
  22 Nov 2023 1 repository listed Syntology ran 10 of 17 samples · 7 unverified
  Precise image segmentation provides clinical study with instructive information.
• CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentation
  8 Nov 2023 1 repository listed
  Both 3D and purely 2D deep learning-based segmentation methods are deficient in dealing with such volumetric data since the performance of 3D methods suffers when confronting anisotropic data, and 2D methods disregard…
• SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images
  23 Oct 2023 1 repository listed Syntology ran 7 of 14 samples · 7 unverified
  In this paper, we introduce SAM-Med3D for general-purpose segmentation on volumetric medical images.
• Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
  17 Oct 2023 1 repository listed Syntology ran 7 of 19 samples · 12 unverified · 19 pointer-only (licence)
  As a result, there is growing interest in using semi-supervised learning (SSL) techniques to train models with limited labeled data.
• Discrepancy Matters: Learning from Inconsistent Decoder Features for Consistent Semi-supervised Medical Image Segmentation
  26 Sep 2023 1 repository listed
  Semi-supervised learning (SSL) has been proven beneficial for mitigating the issue of limited labeled data especially on the task of volumetric medical image segmentation.
• Learnable Weight Initialization for Volumetric Medical Image Segmentation
  15 Jun 2023 1 repository listed
  Hybrid volumetric medical image segmentation models, combining the advantages of local convolution and global attention, have recently received considerable attention.
• Volumetric medical image segmentation through dual self-distillation in U-shaped networks
  5 Jun 2023 1 repository listed
  We attached DSD on several state-of-the-art U-shaped backbones, and extensive experiments on various public 3D medical image segmentation datasets (cardiac substructure, brain tumor and Hippocampus) demonstrated…
• Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ Segmentation
  29 Mar 2023 1 repository listed
  The recent popularity of foundation models and the pre-train-and-adapt paradigm, where a large-scale model is transferred to downstream tasks, is gaining attention for volumetric medical image segmentation.
• Boosting Convolution with Efficient MLP-Permutation for Volumetric Medical Image Segmentation
  23 Mar 2023 1 repository listed
  Recently, the advent of vision Transformer (ViT) has brought substantial advancements in 3D dataset benchmarks, particularly in 3D volumetric medical image segmentation (Vol-MedSeg).
• MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation
  17 Mar 2023 1 repository listed Syntology ran 2 of 4 samples · 2 unverified
  This leads to state-of-the-art performance on 4 tasks on CT and MRI modalities and varying dataset sizes, representing a modernized deep architecture for medical image segmentation.
• MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling
  16 Mar 2023 1 repository listed
  In this study, we introduce Masked Autoencoding and Pseudo-Labeling Segmentation (MAPSeg), a unified UDA framework with great versatility and superior performance for heterogeneous and volumetric medical image…
• Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation
  18 Jun 2022 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Secondly, in fact, they are only partially based on Bayesian deep learning, as their overall architectures are not designed under the Bayesian framework.
• Memory-efficient Segmentation of High-resolution Volumetric MicroCT Images
  31 May 2022 1 repository listed
  In this work, we propose a novel memory-efficient network architecture for 3D high-resolution image segmentation.
• A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation
  26 Nov 2021 1 repository listed Syntology ran 2 of 10 samples · 8 unverified
  We propose a Transformer architecture for volumetric segmentation, a challenging task that requires keeping a complex balance in encoding local and global spatial cues, and preserving information along all axes of the…
• Positional Contrastive Learning for Volumetric Medical Image Segmentation
  16 Jun 2021 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  The success of deep learning heavily depends on the availability of large labeled training sets.
• KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation
  4 Oct 2020 1 repository listed
  To overcome this issue, we propose using an overcomplete convolutional architecture where we project our input image into a higher dimension such that we constrain the receptive field from increasing in the deep layers…
• 3D Densely Convolutional Networks for VolumetricSegmentation
  13 Sep 2017 1 repository listed
  The proposed network architecture provides a dense connection between layers that aims to improve the information flow in the network.

Syntology lines on 12 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.