查看文章

The timely detection and segmentation of pulmonary nodules in lung computed tomography (CT) images can aid in the early diagnosis and treatment of lung cancer. However, manual segmentation of pulmonary nodules by doctors is highly demanding in terms of operational requirements and efficiency. To effectively improve the pulmonary nodule segmentation, this paper proposes a novel neural network, called ResDSda_U-Net, based on the U-Net network with the following improvements: (1) combining a Depthwise Over-parameterized Convolutional layer (DO-Conv) with a simple parameter-free attention module (SimAM), in the form of a newly designed ResDS block; (2) incorporating a denser Dense Atrous Spatial Pyramid Pooling (DASPP) module, between the encoder and decoder, using modified dilated rates to extract multi-scale information more effectively; and (3) adding channel and spatial attention …