Breast cancer, a prevalent and life-threatening disease, necessitates early detection for the effective intervention and the improved patient health outcomes. This paper focuses on the critical problem of identifying breast cancer using a model called Attention U-Net. The model is utilized on the ...
Methods: In this paper, we attempt to solve these limitations and propose the 3D cerebrovascular attention UNet method, named CV-AttentionUNet, for precise extraction of brain vessel images. We proposed a sequence of preprocessing techniques followed by deeply supervised UNet to improve the accuracy ...
Since deep learning is introduced to medical image segmentation, UNet and its variants have been extensively applied in medical image analysis. This paper proposes a multi-scale channel attention UNet (MSCA-UNet) to raise the accuracy of the segmentation in medical ultrasound images. Specifically, a...
Boosting power line inspection in bad weather: Removing weather noise with channel-spatial attention-based UNet doi:10.1007/s11042-023-17554-5Power line inspectionBad weatherImage derainingImage desnowingImage dehazingDatasetPower line inspection based on UAVs can effectively improve the inspection ...
(also called UNet)and attention mechanism, as a strong alternative for seismic event detection and phase picking. On one hand, the utilization of UNet structure enables addressing different levels of deep features. On the other hand, attention mechanism promotes the decoder in the UNet structure ...
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The experiment results demonstrated that, compared with other popular models (ENet, ExFuse, FCN, LinkNet, SegNet, and UNet), for the public dataset, CrackResAttentionNet with BCE loss function and PRelu activation function achieved the best performance in terms of precision (89.40), mean IoU (...
CRAUNet: A cascaded residual attention U-Net for retinal vessel segmentation 2022, Computers in Biology and Medicine Citation Excerpt : Especially, our CRAUNet (Fig. 6(e)) can do better in terms of connectivity and avoid the break of thin vessels. In the following, we compare our CRAUNet ...
In the original U-Net and variant networks based on U-Net (such as TernausNet [41], Res-UNet [42], MultiResUNet [43], and Attention U-Net [39]), the level of pooling in the encoder stage and the level of upsampling in the decoder stage are generally the same, while in AAU-...
然而,在基于UNet的网络中,空间注意力通常被添加到解码/上采样部分的每一层[72–74]。图3显示了在暹罗模型中使用空间和通道注意的示例,尤其是共同注意网络,用于基于建筑物的变化检测[51]。所提出的共同注意网络基于初始关联过程和最终注意模块。对于基于编码和解码模块的GAN网络,添加注意网络的过程与CNN的过程相同,...