LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation *

In this paper, we propose a novel Low-cost U-Net (LCU-Net) for the Environmental Microorganism (EM) image segmentation task to assist microbiologists in detecting and identifying EMs more effectively. The LCU-Net is an improved Convolutional Neural Network (CNN) based on U-Net, Inception, and concatenate operations. It addresses the limitation of single receptive field setting and the relatively high memory cost of U-Net. Experimental results show the effectiveness and potential of the proposed LCU-Net in the practical EM image segmentation field. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

In this paper, a novel Low-cost U-Net (LCU-Net) is proposed for environmental microorganism image segmentation task. The LCU-Net addresses the memory cost issue of traditional U-Net and demonstrates effectiveness and potential in practical application.