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Comparing U-Net convolutional network with mask R-CNN in Nuclei Segmentation


Prof.Dr.E.A.Zanaty,Prof.Dr.Mahmoud M.Abdel-Aty, Khalid abdel-wahab ali


Vol. 22  No. 3  pp. 273-275


Deep Learning is used nowadays in Nuclei segmentation. While recent developments in theory and open-source software have made these tools easier to implement, expert knowledge is still required to choose the exemplary model architecture and training setup. We compare two popular segmentation frameworks, U-Net and Mask-RCNN, in the nuclei segmentation task and find that they have different strengths and failures. we compared both models aiming for the best nuclei segmentation performance. Experimental Results of Nuclei Medical Images Segmentation using U-NET algorithm Outperform Mask R-CNN Algorithm.


U-Net, Mask R-CNN, Nuclei Segmentation.