第三届APTOS竞赛的血管造影报告生成:数据集和基线方法

Weiyi Zhang, Peranut Chotcomwongse, Xiaolan Chen, Florence H.T. Chung, Fan Song, Xueli Zhang, Mingguang He, Danli Shi, Paisan Ruamviboonsuk
{"title":"第三届APTOS竞赛的血管造影报告生成:数据集和基线方法","authors":"Weiyi Zhang, Peranut Chotcomwongse, Xiaolan Chen, Florence H.T. Chung, Fan Song, Xueli Zhang, Mingguang He, Danli Shi, Paisan Ruamviboonsuk","doi":"10.1101/2023.11.26.23299021","DOIUrl":null,"url":null,"abstract":"Fundus angiography, including fundus fluorescein angiography (FFA) and indocyanine green angiography (ICGA), are essential examination tools for visualizing lesions and changes in retinal and choroidal vasculature. However, the interpretation of angiography images is labor-intensive and time-consuming. In response to this, we are organizing the third APTOS competition for automated and interpretable angiographic report generation. For this purpose, we have released the first angiographic dataset, which includes over 50,000 images labeled by retinal specialists. This dataset covers 24 conditions and provides detailed descriptions of the type, location, shape, size and pattern of abnormal fluorescence to enhance interpretability and accessibility. Additionally, we have implemented two baseline methods that achieve an overall score of 7.966 and 7.947 using the classification method and language generation method in the test set, respectively. We anticipate that this initiative will expedite the application of artificial intelligence in automatic report generation, thereby reducing the workload of clinicians and benefiting patients on a broader scale.","PeriodicalId":501390,"journal":{"name":"medRxiv - Ophthalmology","volume":"11 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Angiographic Report Generation for the 3rd APTOS’s Competition: Dataset and Baseline Methods\",\"authors\":\"Weiyi Zhang, Peranut Chotcomwongse, Xiaolan Chen, Florence H.T. Chung, Fan Song, Xueli Zhang, Mingguang He, Danli Shi, Paisan Ruamviboonsuk\",\"doi\":\"10.1101/2023.11.26.23299021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fundus angiography, including fundus fluorescein angiography (FFA) and indocyanine green angiography (ICGA), are essential examination tools for visualizing lesions and changes in retinal and choroidal vasculature. However, the interpretation of angiography images is labor-intensive and time-consuming. In response to this, we are organizing the third APTOS competition for automated and interpretable angiographic report generation. For this purpose, we have released the first angiographic dataset, which includes over 50,000 images labeled by retinal specialists. This dataset covers 24 conditions and provides detailed descriptions of the type, location, shape, size and pattern of abnormal fluorescence to enhance interpretability and accessibility. Additionally, we have implemented two baseline methods that achieve an overall score of 7.966 and 7.947 using the classification method and language generation method in the test set, respectively. We anticipate that this initiative will expedite the application of artificial intelligence in automatic report generation, thereby reducing the workload of clinicians and benefiting patients on a broader scale.\",\"PeriodicalId\":501390,\"journal\":{\"name\":\"medRxiv - Ophthalmology\",\"volume\":\"11 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Ophthalmology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2023.11.26.23299021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Ophthalmology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2023.11.26.23299021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

眼底血管造影,包括眼底荧光素血管造影(FFA)和吲哚菁绿血管造影(ICGA),是观察视网膜和脉络膜血管病变和变化的基本检查工具。然而,血管造影图像的解释是劳动密集型和耗时的。为此,我们正在组织第三届APTOS自动和可解释的血管造影报告生成竞赛。为此,我们发布了第一个血管造影数据集,其中包括超过50,000张由视网膜专家标记的图像。该数据集涵盖了24种情况,并提供了异常荧光的类型、位置、形状、大小和模式的详细描述,以增强可解释性和可访问性。此外,我们在测试集中使用分类方法和语言生成方法实现了两种基线方法,分别获得了7.966和7.947的总分。我们预计这一举措将加快人工智能在自动报告生成中的应用,从而减少临床医生的工作量,并在更大范围内使患者受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Angiographic Report Generation for the 3rd APTOS’s Competition: Dataset and Baseline Methods
Fundus angiography, including fundus fluorescein angiography (FFA) and indocyanine green angiography (ICGA), are essential examination tools for visualizing lesions and changes in retinal and choroidal vasculature. However, the interpretation of angiography images is labor-intensive and time-consuming. In response to this, we are organizing the third APTOS competition for automated and interpretable angiographic report generation. For this purpose, we have released the first angiographic dataset, which includes over 50,000 images labeled by retinal specialists. This dataset covers 24 conditions and provides detailed descriptions of the type, location, shape, size and pattern of abnormal fluorescence to enhance interpretability and accessibility. Additionally, we have implemented two baseline methods that achieve an overall score of 7.966 and 7.947 using the classification method and language generation method in the test set, respectively. We anticipate that this initiative will expedite the application of artificial intelligence in automatic report generation, thereby reducing the workload of clinicians and benefiting patients on a broader scale.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信