LUNG CT SEGMENTATION ALGORITHM BASED ON RDU-NET NETWORK
This paper proposes the RDU-Net network to segment lung nodules.The network is based on the U-Net network.Aimed at the phenomenon of gradient disappearance that often occurred during network training,the residual unit was introduced to improve the basic network.This operation solved the problem of gradient disappearance during the network model training process.In order to improve the generalization ability of the network,a Dropout layer was added to the network to avoid overfitting during the training process and further improve the segmentation accuracy.The network was tested on the LIDC-IDRI dataset,and its AUC and Dice reached 0.89 and 0.76,respectively.Compared with the basic network,its segmentation accuracy and segmentation effect were improved to a certain extent.
Deep learningU-NetLung slice segmentationLung nodules
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