Lung Nodule Detection Method Based on Improved U-Net Network
LI Zimeng
ZHAO Jiantao
Abstract：In order to solve the problem of huge workload brought to doctors by huge lung CT data,this paper proposes a lung nodule detection method based on improved U-Net network.The method in this paper takes the U-Net network as the basic frame-work.Firstly,residual modules are added to the coding part to increase the depth of the network.Then,the deep supervision module is added to the decoding part,so that the shallow layer can be more fully trained.Finally,the attention mechanism module is used between the encoding and decoding parts to make the model more focused on learning useful information.The experimental results show that the method in this paper has better performance than other detection methods,and the Dice coefficient,sensitivity and specificity on the public LUNA 16 dataset are 0.8109,90.62%and 98.97%,respectively.
Keywords：detection of pulmonary nodulesdeep supervisionattention mechanismresidual network
Publication Date：2025-12-20
Online Publishing Date：2026-03-09(First online date of this platform, not the publication date of the document)
Pages：5( 3590-3594 )