Cardiac Segmentation

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

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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

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 40 papers with code (88 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.

• TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
  8 Feb 2021 22 repositories listed Syntology ran 6 of 7 samples · 1 unverified · 7 pointer-only (licence)
  Medical image segmentation is an essential prerequisite for developing healthcare systems, especially for disease diagnosis and treatment planning.
• Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation
  12 May 2021 7 repositories listed Syntology ran 3 of 18 samples · 15 unverified
  In the past few years, convolutional neural networks (CNNs) have achieved milestones in medical image analysis.
• Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
  20 Jul 2020 4 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  Few-shot semantic segmentation (FSS) has great potential for medical imaging applications.
• Towards Robust Cardiac Segmentation using Graph Convolutional Networks
  2 Oct 2023 3 repositories listed
  We propose a graph architecture that uses two convolutional rings based on cardiac anatomy and show that this eliminates anatomical incorrect multi-structure segmentations on the publicly available CAMUS dataset.
• A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI
  2 Apr 2016 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  To our knowledge, this is the first application of a fully convolutional neural network architecture for pixel-wise labeling in cardiac magnetic resonance imaging.
• Weak-Mamba-UNet: Visual Mamba Makes CNN and ViT Work Better for Scribble-based Medical Image Segmentation
  16 Feb 2024 2 repositories listed Syntology ran 5 of 5 samples · 0 unverified · 4 pointer-only (licence)
  Medical image segmentation is increasingly reliant on deep learning techniques, yet the promising performance often come with high annotation costs.
• Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation
  12 Apr 2021 2 repositories listed
  Deep learning methods have reached state-of-the-art performance in cardiac image segmentation.
• Disentangle, align and fuse for multimodal and semi-supervised image segmentation
  11 Nov 2019 2 repositories listed
  Core to our method is learning a disentangled decomposition into anatomical and imaging factors.
• PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation
  19 Dec 2018 2 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  In this paper, we propose the PnPAdaNet (plug-and-play adversarial domain adaptation network) for adapting segmentation networks between different modalities of medical images, e.
• GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation
  6 Jan 2025 1 repository listed
  Vision Transformers (ViTs) have shown promise in medical image semantic segmentation (MISS) by capturing long-range correlations.
• RotCAtt-TransUNet++: Novel Deep Neural Network for Sophisticated Cardiac Segmentation
  9 Sep 2024 1 repository listed
  However, existing state-of-the-art (SOTA) neural networks, including both CNN-based and Transformer-based approaches, exhibit limitations in practical applicability due to their inability to effectively capture…
• CAMS: Convolution and Attention-Free Mamba-based Cardiac Image Segmentation
  9 Jun 2024 1 repository listed
  Convolutional Neural Networks (CNNs) and Transformer-based self-attention models have become the standard for medical image segmentation.
• Direct Cardiac Segmentation from Undersampled K-space Using Transformers
  31 May 2024 1 repository listed
  The prevailing deep learning-based methods of predicting cardiac segmentation involve reconstructed magnetic resonance (MR) images.
• LUCF-Net: Lightweight U-shaped Cascade Fusion Network for Medical Image Segmentation
  11 Apr 2024 1 repository listed
  In this study, the performance of existing U-shaped neural network architectures was enhanced for medical image segmentation by adding Transformer.
• Deep Separable Spatiotemporal Learning for Fast Dynamic Cardiac MRI
  24 Feb 2024 1 repository listed
  This challenge necessitates extensive training data in deep learning reconstruction methods.
• Semi-Mamba-UNet: Pixel-Level Contrastive and Pixel-Level Cross-Supervised Visual Mamba-based UNet for Semi-Supervised Medical Image Segmentation
  11 Feb 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Medical image segmentation is essential in diagnostics, treatment planning, and healthcare, with deep learning offering promising advancements.
• Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation
  7 Feb 2024 1 repository listed Syntology ran 5 of 5 samples · 0 unverified
  Mamba-UNet adopts a pure Visual Mamba (VMamba)-based encoder-decoder structure, infused with skip connections to preserve spatial information across different scales of the network.
• NISF: Neural Implicit Segmentation Functions
  15 Sep 2023 1 repository listed
  Approaches that rely on convolutional neural networks (CNNs) are limited to grid-like inputs and not easily applicable to sparse or partial measurements.
• AC-Norm: Effective Tuning for Medical Image Analysis via Affine Collaborative Normalization
  28 Jul 2023 1 repository listed
  Driven by the latest trend towards self-supervised learning (SSL), the paradigm of "pretraining-then-finetuning" has been extensively explored to enhance the performance of clinical applications with limited annotations.
• Echo from noise: synthetic ultrasound image generation using diffusion models for real image segmentation
  9 May 2023 1 repository listed
  We propose a novel pipeline for the generation of synthetic ultrasound images via Denoising Diffusion Probabilistic Models (DDPMs) guided by cardiac semantic label maps.
• Self-Supervised Pretraining for 2D Medical Image Segmentation
  1 Sep 2022 1 repository listed
  In this paper, we elaborate and analyse the effectiveness of supervised and self-supervised pretraining approaches on downstream medical image segmentation, focusing on convergence and data efficiency.
• ShapePU: A New PU Learning Framework Regularized by Global Consistency for Scribble Supervised Cardiac Segmentation
  5 Jun 2022 1 repository listed
  To tackle this problem, we propose a new scribble-guided method for cardiac segmentation, based on the Positive-Unlabeled (PU) learning framework and global consistency regularization, and termed as ShapePU.
• Test-Time Adaptation with Shape Moments for Image Segmentation
  16 May 2022 1 repository listed
  In typical clinical settings, the source data is inaccessible and the target distribution is represented with a handful of samples: adaptation can only happen at test time on a few or even a single subject(s).
• Unsupervised Domain Adaptation for Cardiac Segmentation: Towards Structure Mutual Information Maximization
  20 Apr 2022 1 repository listed
  This paper introduces UDA-VAE++, an unsupervised domain adaptation framework for cardiac segmentation with a compact loss function lower bound.
• Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels
  3 Mar 2022 1 repository listed Syntology ran 0 of 2 samples · 2 unverified
  Motivated by this, and the observation that the foreground class (e.
• Continual Active Learning Using Pseudo-Domains for Limited Labelling Resources and Changing Acquisition Characteristics
  25 Nov 2021 1 repository listed
  Here, we propose a method for continual active learning operating on a stream of medical images in a multi-scanner setting.
• MISSFormer: An Effective Medical Image Segmentation Transformer
  15 Sep 2021 1 repository listed
  The CNN-based methods have achieved impressive results in medical image segmentation, but it failed to capture the long-range dependencies due to the inherent locality of convolution operation.
• Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation
  7 Aug 2021 1 repository listed
  The success of neural networks on medical image segmentation tasks typically relies on large labeled datasets for model training.
• Source-Free Domain Adaptation for Image Segmentation
  6 Aug 2021 1 repository listed
  Our method yields comparable results to several state of the art adaptation techniques, despite having access to much less information, as the source images are entirely absent in our adaptation phase.
• Margin Preserving Self-paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation
  15 Mar 2021 1 repository listed
  To bridge the gap between the source and target domains in unsupervised domain adaptation (UDA), the most common strategy puts focus on matching the marginal distributions in the feature space through adversarial…

Syntology lines on 9 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.