Therefore, this paper proposes PA UNET++ to enhance the segmentation of multiple targets and uses the segmentation results of thyroid ultrasound multi-tissue to achieve three-dimensional visualization. This visualization clearly represents the various tissues and their spatial relationships....
First, adaptive fusion is applied to the features of each layer of the encoder, enabling the AFFM module to adaptively select appropriate features for fusion based on the size and characteristics of the tumor in the CT image. This ensures that the detailed information at each encoder stage is...
and then a feature fusion strategy with a pyramid structure is used, with layers fused from low to high, to obtain richer contextual information, so that each layer of the layered feature maps has original semantic information
In the domain of mangrove image segmentation [38], the UNet-based neural network model has garnered substantial acclaim. UNet leverages both spatial and spectral information to facilitate semantic segmentation through an encoder-decoder architecture. As an illustration of this paradigm, Dong et al. [...
Such a design has two advantages: (1) 3 × 3 convolution kernel that captures the eight-neighborhood information of pixels is the smallest kernel size. The combination of three 3 × 3 convolutional layers has a smaller number of parameters than one 7 × 7 convolutional layer, leading to its...
While FPN [24] can overcome these drawbacks to retain multi-scale contextual information by using multiple prediction layers: one for each up-sampling layer. Based on this idea, we propose a novel segmentation scheme for the infections of COVID-19. Fig. 2 illustrates the proposed network ...
CODE:https://github.com/mindflow-institue/TransCeption cnn缺少长距离依赖,最近的一些工作用了transformer来解决,还有一些工作扩展了u-net的多尺度特征提取和fusion,但是都有一定的缺陷 如: unet和transformer结合的方法: 低维特征和高维特征不能在transformer中充分融合,多级的特征之间还有交互的余地。
Then, in each layer of the encoder sub-network, we propose a newly pyramid edge enhancement module with edge-related prior knowledge to obtain the edge multi-granularity information, which enhances the accuracy of the segmentation boundary. In the BCF-UNet, edge information is peculiarly utilized ...
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For the second baseline model, we used a CTPA-based vision Transformer (ViT) model. ViT model was developed to transfer the success of the self-attention mechanism on NLP tasks into imaging applications58. Specifically, we applied Nvidia’s Swin UNETR59. Swin UNETR (Shifting windows Unet Transf...