解放军医学院学报2025，Vol.46Issue(2)：153-160,8.DOI:10.12435/j.issn.2095-5227.24070104
医学影像跨模态生成方法综述
Review of medical imaging cross-modal generation methods
摘要
Abstract
In the rapidly developing field of medical artificial intelligence,image generation algorithm based on deep learning has become one of the research hotspots.This paper aims to review the status quos of four major image generation algorithms,namely autoregressive model,variational autoencoder,generative adversarial network and diffusion model,and analyze the application of generative model in medical multimodal image conversion from three modes:computed tomography,magnetic resonance imaging and computed tomography angiography.The generative model not only has broad application prospects in the field of medical imaging,but also has great value potential.关键词
深度学习/图像模态/医学影像/人工智能/神经网络Key words
deep learning/imaging modalities/medical imaging/artificial intelligence/neural networks分类
医药卫生引用本文复制引用
花芸,康敏诗,刘盼,郭华源,金晓宇,李轶玮,何昆仑..医学影像跨模态生成方法综述[J].解放军医学院学报,2025,46(2):153-160,8.基金项目
新一代人工智能国家科技重大专项资助(2021ZD0140408) （2021ZD0140408）
