{"title":"根据文字提示合成胸部 X 光图像","authors":"Daniel Truhn, Jakob Nikolas Kather","doi":"10.1038/s41551-024-01261-z","DOIUrl":null,"url":null,"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.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"19 1","pages":""},"PeriodicalIF":26.8000,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Synthetic chest X-ray images from text prompts\",\"authors\":\"Daniel Truhn, Jakob Nikolas Kather\",\"doi\":\"10.1038/s41551-024-01261-z\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":19063,\"journal\":{\"name\":\"Nature Biomedical Engineering\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":26.8000,\"publicationDate\":\"2024-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Biomedical Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1038/s41551-024-01261-z\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Biomedical Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1038/s41551-024-01261-z","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
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.
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.
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