电子科技2026，Vol.39Issue(6)：25-31,7.DOI:10.16180/j.cnki.issn1007-7820.2026.06.003
基于引入注意力机制扩散模型的儿童头颅CT生成研究
Research on CT Generation of Children's Skull Based on the Diffusion Model of Attention Mechanism
摘要
Abstract
In view of the difficulty in obtaining medical images and the deficiencies of traditional generative models,an improved diffusion model CBOM-MDDPM(Diffusion Probabilistic Model Enhanced with Convolutional Block Attention Module and MobileNetV3)based on depth-separable convolutional MobileNetV3 and the attention mechanism is proposed.The 463 cases of children's skull CT(Computed Tomography)data provided by Xinhua Hos-pital Affiliated to Shanghai Jiao Tong University are taken as the image training set.By integrating the bneck module in MobileNetV3 into the UNet(U-shaped Network)encoding part of the diffusion model and introducing the CBAM attention mechanism and other strategies in its downsampling part,the computational burden is reduced,and the im-age generation quality and sampling speed are improved.The experimental results show that the FID(Frechet Incep-tion Distance)and IS(Inception Score)indicators of the proposed model are 38.92±1.06 and 2.25±0.035 respec-tively,and the quality of the generated images is superior to that of the traditional GAN(Generative Adversarial Net-work)model.Compared with the DDPM(Denoising Diffusion Probabilistic Mode)model,the number of parameters of the CBAM-MDDPM model has decreased by 38 percentage points,and the processing speed has increased by 58 percentage points,which proves the effectiveness of the proposed algorithm.关键词
医学图像生成/深度学习/扩散模型/MobileNetV3/注意力机制/UNet/模型轻量化/特征提取Key words
medical image generation/deep learning/diffusion model/MobileNetV3/attention mechanism/UNet/lightweight model/feature extraction分类
信息技术与安全科学引用本文复制引用
薛立哲,林勇..基于引入注意力机制扩散模型的儿童头颅CT生成研究[J].电子科技,2026,39(6):25-31,7.基金项目
国家自然科学基金(81801797)National Natural Science Foundation of China(81801797) （81801797）
