Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge
The emergence of deep learning has considerably advanced the state-of-the-art in cardiac
magnetic resonance (CMR) segmentation. Many techniques have been proposed over the …
magnetic resonance (CMR) segmentation. Many techniques have been proposed over the …
[HTML][HTML] From accuracy to reliability and robustness in cardiac magnetic resonance image segmentation: a review
Since the rise of deep learning (DL) in the mid-2010s, cardiac magnetic resonance (CMR)
image segmentation has achieved state-of-the-art performance. Despite achieving inter …
image segmentation has achieved state-of-the-art performance. Despite achieving inter …
Attention-guided residual W-Net for supervised cardiac magnetic resonance imaging segmentation
Objective With latest developments in deep learning approaches, automated, accurate, fast,
and generalized segmentation model for left atrium, left ventricle, right ventricle, and …
and generalized segmentation model for left atrium, left ventricle, right ventricle, and …
SC-SSL: Self-correcting Collaborative and Contrastive Co-training Model for Semi-Supervised Medical Image Segmentation
Image segmentation achieves significant improvements with deep neural networks at the
premise of a large scale of labeled training data, which is laborious to assure in medical …
premise of a large scale of labeled training data, which is laborious to assure in medical …
TSP-UDANet: two-stage progressive unsupervised domain adaptation network for automated cross-modality cardiac segmentation
Accurate segmentation of cardiac anatomy is a prerequisite for the diagnosis of
cardiovascular disease. However, due to differences in imaging modalities and imaging …
cardiovascular disease. However, due to differences in imaging modalities and imaging …
W-Net: Novel deep supervision for deep learning-based cardiac magnetic resonance imaging segmentation
Cardiac magnetic resonance imaging (CMRI) segmentation transforms cardiac MR images
into semantic regions to define the left ventricle cavity, right ventricle cavity, and …
into semantic regions to define the left ventricle cavity, right ventricle cavity, and …
IRA-Unet: inception residual attention unet in adversarial network for cardiac MRI segmentation
A Motamedi - Authorea Preprints, 2023 - techrxiv.org
IRA-Unet: Inception Residual Attention Unet in Adversarial Network for Cardiac MRI
Segmentation Page 1 P osted on 10 Aug 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech …
Segmentation Page 1 P osted on 10 Aug 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech …
An Unsupervised Domain Adaptation Model Based on Multi-Level Joint Alignment for Multi-Modal Cardiac Image Segmentation
Abstract Unsupervised Domain Adaptation has greatly boosted the performance of multi-
modal medical segmentation when there are only source domain labels and no labels in the …
modal medical segmentation when there are only source domain labels and no labels in the …
Segmentation of Multi-Center Cardiac Magnetic Resonance Images Based on Improved DeepLabV3+
J Hou, H Shao, W Cui - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
The clinical assessment of multiple cardiovascular illnesses necessitates the accurate
segmentation of cardiac magnetic resonance (CMR) images. CMR images have the …
segmentation of cardiac magnetic resonance (CMR) images. CMR images have the …
Automatic Segmentation of Left Ventricle in Cardiac Magnetic Resonance Images
Segmentation of the left ventricle in cardiac magnetic resonance imaging MRI scans
enables cardiologists to calculate the volume of the left ventricle and subsequently its …
enables cardiologists to calculate the volume of the left ventricle and subsequently its …