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Accurately segmented nuclei are important, not only for cancer classification, but also for predicting treatment effectiveness and other biomedical applications. However, the diversity of cell types, various external factors, and illumination conditions make nucleus segmentation a challenging task. In this work, we present a new deep learning-based method for cell nucleus segmentation. The proposed convolutional blur attention (CBA) network consists of downsampling and upsampling procedures. Adoi:10.3390/s22041586 pmid:35214488 pmcid:PMC8878074 fatcat:xpnkecco5zclrccsiw6tmaocoi