A survey on attention mechanisms for medical applications: are we moving toward better algorithms?

T Gonçalves, I Rio-Torto, LF Teixeira… - IEEE Access, 2022 - ieeexplore.ieee.org
The increasing popularity of attention mechanisms in deep learning algorithms for computer
vision and natural language processing made these models attractive to other research …

Attention mechanisms in medical image segmentation: A survey

Y **e, B Yang, Q Guan, J Zhang, Q Wu… - arxiv preprint arxiv …, 2023 - arxiv.org
Medical image segmentation plays an important role in computer-aided diagnosis. Attention
mechanisms that distinguish important parts from irrelevant parts have been widely used in …

DR-VNet: retinal vessel segmentation via dense residual UNet

A Karaali, R Dahyot, DJ Sexton - International Conference on Pattern …, 2022 - Springer
Accurate retinal vessel segmentation is an important task for many computer-aided
diagnosis systems. Yet, it is still a challenging problem due to the complex vessel structures …

[HTML][HTML] MTPA_Unet: Multi-scale transformer-position attention retinal vessel segmentation network joint transformer and CNN

Y Jiang, J Liang, T Cheng, X Lin, Y Zhang, J Dong - Sensors, 2022 - mdpi.com
Retinal vessel segmentation is extremely important for risk prediction and treatment of many
major diseases. Therefore, accurate segmentation of blood vessel features from retinal …

BCR-UNet: Bi-directional ConvLSTM residual U-Net for retinal blood vessel segmentation

Y Yi, C Guo, Y Hu, W Zhou, W Wang - Frontiers in Public Health, 2022 - frontiersin.org
Background High precision segmentation of retinal blood vessels from retinal images is a
significant step for doctors to diagnose many diseases such as glaucoma and …

Advances in attention mechanisms for medical image segmentation

J Zhang, X Chen, B Yang, Q Guan, Q Chen… - Computer Science …, 2025 - Elsevier
Medical image segmentation plays an important role in computer-aided diagnosis. Attention
mechanisms that distinguish important parts from irrelevant parts have been widely used in …

Robust segmentation of vascular network using deeply cascaded AReN-UNet

AA Rahman, B Biswal, S Hasan, MVS Sairam - … Signal Processing and …, 2021 - Elsevier
Retinal vessel segmentation is an essential step for non-invasive diagnosis and analysis of
ocular pathologies such as diabetic retinopathy, glaucoma, etc. Although several deep …

Atrous residual convolutional neural network based on U-Net for retinal vessel segmentation

J Wu, Y Liu, Y Zhu, Z Li - PLoS One, 2022 - journals.plos.org
Extracting features of retinal vessels from fundus images plays an essential role in computer-
aided diagnosis of diseases, such as diabetes, hypertension, and cerebrovascular diseases …

SERR‐U‐Net: Squeeze‐and‐Excitation Residual and Recurrent Block‐Based U‐Net for Automatic Vessel Segmentation in Retinal Image

J Wang, X Li, P Lv, C Shi - Computational and Mathematical …, 2021 - Wiley Online Library
Background and Objective. Accurate segmentation of retinal vessels is considered as an
important prerequisite for computer‐aided diagnosis of ophthalmic diseases, diabetes …

LC-MANet: Location-constrained joint optic disc and cup segmentation via multiplex aggregation network

J Yu, N Chen, J Li, L Xue, R Chen, C Yang… - Computers and …, 2024 - Elsevier
Many early ophthalmology-related diseases can be detected through fundus images. The
cup-to-disc ratio (CDR) is an important criterion for the early screening and diagnosis of …