Cardiac Segmentation

29 papers with code • 0 benchmarks • 3 datasets

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Most implemented papers

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Beckschen/TransUNet 8 Feb 2021

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

HuCaoFighting/Swin-Unet 12 May 2021

In the past few years, convolutional neural networks (CNNs) have achieved milestones in medical image analysis.

A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI

vuptran/cardiac-segmentation 2 Apr 2016

To our knowledge, this is the first application of a fully convolutional neural network architecture for pixel-wise labeling in cardiac magnetic resonance imaging.

PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation

carrenD/Med-CMDA 19 Dec 2018

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. g., MRI and CT. We propose to tackle the significant domain shift by aligning the feature spaces of source and target domains in an unsupervised manner.

Disentangle, align and fuse for multimodal and semi-supervised image segmentation

vios-s/multimodal_segmentation 11 Nov 2019

Core to our method is learning a disentangled decomposition into anatomical and imaging factors.

Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation

robustml-eurecom/quality_control_CMR 12 Apr 2021

Deep learning methods have reached state-of-the-art performance in cardiac image segmentation.

3D Consistent & Robust Segmentation of Cardiac Images by Deep Learning with Spatial Propagation

julien-zheng/CardiacSegmentationPropagation 25 Apr 2018

We propose a method based on deep learning to perform cardiac segmentation on short axis MRI image stacks iteratively from the top slice (around the base) to the bottom slice (around the apex).

Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences

cq615/Joint-Motion-Estimation-and-Segmentation 11 Jun 2018

Cardiac motion estimation and segmentation play important roles in quantitatively assessing cardiac function and diagnosing cardiovascular diseases.

Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow

julien-zheng/CardiacMotionFlow 8 Nov 2018

We propose a method to classify cardiac pathology based on a novel approach to extract image derived features to characterize the shape and motion of the heart.