Synthetic chest X-ray images from text prompts

IF 26.8 1区医学 Q1 ENGINEERING, BIOMEDICAL

Nature Biomedical Engineering Pub Date : 2024-10-07 DOI:10.1038/s41551-024-01261-z

Daniel Truhn, Jakob Nikolas Kather

引用次数: 0

Abstract

A latent diffusion model pre-trained on pairs of natural images and text descriptors can be adapted to generate realistic chest radiographs that are controlled by free-form medical text prompts.

Abstract Image

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根据文字提示合成胸部 X 光图像

在自然图像和文本描述符对上预先训练的潜在扩散模型可用于生成由自由格式医学文本提示控制的逼真胸片。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature Biomedical Engineering Medicine-Medicine (miscellaneous)

CiteScore

45.30

自引率

1.10%

发文量

138

期刊介绍： Nature Biomedical Engineering is an online-only monthly journal that was launched in January 2017. It aims to publish original research, reviews, and commentary focusing on applied biomedicine and health technology. The journal targets a diverse audience, including life scientists who are involved in developing experimental or computational systems and methods to enhance our understanding of human physiology. It also covers biomedical researchers and engineers who are engaged in designing or optimizing therapies, assays, devices, or procedures for diagnosing or treating diseases. Additionally, clinicians, who make use of research outputs to evaluate patient health or administer therapy in various clinical settings and healthcare contexts, are also part of the target audience.