PCCA-Model: An Attention Module for Medical Image Segmentation

Convolutional neural networks have been increasingly employed in the field of medical image segmentation. Based on this idea that the human visual cortex differs in terms of the size of the receptive field and can sense the stimulus location., we proposed the pyramid channel coordinate attention (PCCA) module to fuse multiscale features in the channel direction, aggregate local and global channel information, combine them with the location information in the spatial direction, and then integrate them into the existing semantic segmentation network. We conducted numerous experiments on the datasets, namely LiTS, ISIC-2018, and CX, and obtained state-of-the-art results

Additional file 4 of A comparative study of the prevalence of myopia and behavioral changes in primary school students

Additional file 4: SupplementaryTable 3.Comparison of behaviorsrelated to myopia between the twoCohorts according to ag

Additional file 3 of A comparative study of the prevalence of myopia and behavioral changes in primary school students

Additional file 3: Supplementary Table 2. Comparison ofbehaviors related to myopia between boys or girls in two group

Additional file 1 of A comparative study of the prevalence of myopia and behavioral changes in primary school students

Additional file 1

Additional file 2 of A comparative study of the prevalence of myopia and behavioral changes in primary school students

Additional file 2: SupplementaryTable 1.Comparison of SER and AL (AL/CR) in myopia or non-myopia between two groups