Alan V Godfrey, Melissa L Rosado-de-Christenson, Alan P Wimmer, Sherief H Garrana, Santiago Martínez-Jiménez
{"title":"Radiography of Contemporary Cardiac Devices.","authors":"Alan V Godfrey, Melissa L Rosado-de-Christenson, Alan P Wimmer, Sherief H Garrana, Santiago Martínez-Jiménez","doi":"10.1148/rg.250039","DOIUrl":"https://doi.org/10.1148/rg.250039","url":null,"abstract":"","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"45 9","pages":"e250039"},"PeriodicalIF":5.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Melanie P Caserta, Rachel L Perez, Dillon M Brown, Cameron R Adler, Madhura A Desai, Jordan D LeGout, Mary Jennings Clingan, Anil Nicholas Kurup, Jacob N Clendenon, Shennen A Mao, Nirvikar Dahiya, Lauren F Alexander
{"title":"Invited Commentary: Ancillary US of the Bowel for Improved Patient Care and Management.","authors":"Richard G Barr","doi":"10.1148/rg.240256","DOIUrl":"10.1148/rg.240256","url":null,"abstract":"","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"45 9","pages":"e240256"},"PeriodicalIF":5.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An Ni Wu, Merve Kulbay, Phillip M Cheng, Alexandre Cadrin-Chênevert, Laurent Létourneau-Guillon, Gabriel Chartrand, Jaron Chong, Emmanuel Montagnon, Ismail Ben Ayed, An Tang
In radiology practice, medical images are described and interpreted by radiologists in text reports. Recent technical developments enabling deep learning models to connect images and text may facilitate the radiologic workflow. These developments include advances in data embedding, self-supervised learning, zero-shot learning, and transformer-based model architectures. Models connecting images and text can be divided into four categories: (a) Text-image alignment models associate text descriptions with corresponding images. (b) Image-to-text models create text descriptions from images. (c) Text-to-image models generate images from text descriptions. (d) Multimodal models integrate and interpret multiple types of data such as images, videos, text, and numbers simultaneously. Potential clinical applications of these models include automated captioning of medical images, generation of the preliminary radiology report, and creation of educational images. These advances may enable case prioritization, streamlining of clinical workflows, and improvements in diagnostic accuracy. Published under a CC BY 4.0 license.
在放射学实践中,医学图像是由放射科医生在文本报告中描述和解释的。最近的技术发展使深度学习模型能够连接图像和文本,这可能会促进放射学工作流程。这些发展包括数据嵌入、自监督学习、零学习和基于变压器的模型架构方面的进展。连接图像和文本的模型可以分为四类:(a)文本-图像对齐模型将文本描述与相应的图像关联起来。(b)图像到文本模型从图像创建文本说明。(c)文本到图像模型从文本说明生成图像。(d)多模态模型同时整合和解释多种类型的数据,如图像、视频、文本和数字。这些模型的潜在临床应用包括医学图像的自动字幕、初步放射学报告的生成和教育图像的创建。这些进步可能使病例优先排序,简化临床工作流程,并提高诊断准确性。在CC BY 4.0许可下发布。
{"title":"Deep Learning Models Connecting Images and Text: A Primer for Radiologists.","authors":"An Ni Wu, Merve Kulbay, Phillip M Cheng, Alexandre Cadrin-Chênevert, Laurent Létourneau-Guillon, Gabriel Chartrand, Jaron Chong, Emmanuel Montagnon, Ismail Ben Ayed, An Tang","doi":"10.1148/rg.240103","DOIUrl":"10.1148/rg.240103","url":null,"abstract":"<p><p>In radiology practice, medical images are described and interpreted by radiologists in text reports. Recent technical developments enabling deep learning models to connect images and text may facilitate the radiologic workflow. These developments include advances in data embedding, self-supervised learning, zero-shot learning, and transformer-based model architectures. Models connecting images and text can be divided into four categories: <i>(a)</i> Text-image alignment models associate text descriptions with corresponding images. <i>(b)</i> Image-to-text models create text descriptions from images. <i>(c)</i> Text-to-image models generate images from text descriptions. <i>(d)</i> Multimodal models integrate and interpret multiple types of data such as images, videos, text, and numbers simultaneously. Potential clinical applications of these models include automated captioning of medical images, generation of the preliminary radiology report, and creation of educational images. These advances may enable case prioritization, streamlining of clinical workflows, and improvements in diagnostic accuracy. Published under a CC BY 4.0 license.</p>","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"45 9","pages":"e240103"},"PeriodicalIF":5.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144857050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Somiah E Almeky, Franklin Iheanacho, Priscilla J Slanetz, Anand K Narayan, Lucy B Spalluto, Arun Krishnaraj, Carla Brathwaite, Farouk Dako, Randy C Miles, Daniel B Chonde, Gwendolyn M Bryant-Smith, Christina Alexandra LeBedis, Efrén J Flores