Acc-unet: A completely convolutional unet model for the 2020s

N Ibtehaz, D Kihara - … Conference on Medical Image Computing and …, 2023 - Springer
This decade is marked by the introduction of Vision Transformer, a radical paradigm shift in
broad computer vision. A similar trend is followed in medical imaging, UNet, one of the most …

AMSUnet: A neural network using atrous multi-scale convolution for medical image segmentation

Y Yin, Z Han, M Jian, GG Wang, L Chen… - Computers in Biology and …, 2023 - Elsevier
In recent years, Unet and its variants have gained astounding success in the realm of
medical image processing. However, some Unet variant networks enhance their …

Tmd-unet: Triple-unet with multi-scale input features and dense skip connection for medical image segmentation

ST Tran, CH Cheng, TT Nguyen, MH Le, DG Liu - Healthcare, 2021 - mdpi.com
Deep learning is one of the most effective approaches to medical image processing
applications. Network models are being studied more and more for medical image …

DC-UNet: rethinking the U-Net architecture with dual channel efficient CNN for medical image segmentation

A Lou, S Guan, M Loew - Medical Imaging 2021: Image …, 2021 - spiedigitallibrary.org
Recently, deep learning has become much more popular in computer vision applications.
The Convolutional Neural Network (CNN) has brought a breakthrough in image …

Narrowing the semantic gaps in u-net with learnable skip connections: The case of medical image segmentation

H Wang, P Cao, J Yang, O Zaiane - Neural Networks, 2024 - Elsevier
Current state-of-the-art medical image segmentation techniques predominantly employ the
encoder–decoder architecture. Despite its widespread use, this U-shaped framework …

DA-TransUNet: integrating spatial and channel dual attention with transformer U-net for medical image segmentation

G Sun, Y Pan, W Kong, Z Xu, J Ma… - … in Bioengineering and …, 2024 - frontiersin.org
Accurate medical image segmentation is critical for disease quantification and treatment
evaluation. While traditional U-Net architectures and their transformer-integrated variants …

3d transunet: Advancing medical image segmentation through vision transformers

J Chen, J Mei, X Li, Y Lu, Q Yu, Q Wei, X Luo… - arXiv preprint arXiv …, 2023 - arxiv.org
Medical image segmentation plays a crucial role in advancing healthcare systems for
disease diagnosis and treatment planning. The u-shaped architecture, popularly known as …

Bi-directional ConvLSTM U-Net with densley connected convolutions

R Azad, M Asadi-Aghbolaghi… - Proceedings of the …, 2019 - openaccess.thecvf.com
In recent years, deep learning-based networks have achieved state-of-the-art performance
in medical image segmentation. Among the existing networks, U-Net has been successfully …

U-Net v2: Rethinking the skip connections of U-Net for medical image segmentation

Y Peng, M Sonka, DZ Chen - arXiv preprint arXiv:2311.17791, 2023 - arxiv.org
In this paper, we introduce U-Net v2, a new robust and efficient U-Net variant for medical
image segmentation. It aims to augment the infusion of semantic information into low-level …

[HTML][HTML] DCSAU-Net: A deeper and more compact split-attention U-Net for medical image segmentation

Q Xu, Z Ma, HE Na, W Duan - Computers in Biology and Medicine, 2023 - Elsevier
Deep learning architecture with convolutional neural network achieves outstanding success
in the field of computer vision. Where U-Net has made a great breakthrough in biomedical …