胎儿超声结构的缩放模式特征。

Mohammad Alsharid, Robail Yasrab, Lior Drukker, Aris T Papageorghiou, J Alison Noble
{"title":"胎儿超声结构的缩放模式特征。","authors":"Mohammad Alsharid, Robail Yasrab, Lior Drukker, Aris T Papageorghiou, J Alison Noble","doi":"10.1007/978-3-031-72083-3_73","DOIUrl":null,"url":null,"abstract":"<p><p>During a fetal ultrasound scan, a sonographer will zoom in and zoom out as they attempt to get clearer images of the anatomical structures of interest. This paper explores how to use this zoom information which is an under-utilised piece of information that is extractable from fetal ultrasound images. We explore associating zooming patterns to specific structures. The presence of such patterns would indicate that each individual anatomical structure has a unique signature associated with it, thereby allowing for classification of fetal ultrasound clips without directly reading the actual fetal ultrasound images in a convolutional neural network.</p>","PeriodicalId":94280,"journal":{"name":"Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention","volume":"15004 ","pages":"786-795"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7616787/pdf/","citationCount":"0","resultStr":"{\"title\":\"Zoom Pattern Signatures for Fetal Ultrasound Structures.\",\"authors\":\"Mohammad Alsharid, Robail Yasrab, Lior Drukker, Aris T Papageorghiou, J Alison Noble\",\"doi\":\"10.1007/978-3-031-72083-3_73\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>During a fetal ultrasound scan, a sonographer will zoom in and zoom out as they attempt to get clearer images of the anatomical structures of interest. This paper explores how to use this zoom information which is an under-utilised piece of information that is extractable from fetal ultrasound images. We explore associating zooming patterns to specific structures. The presence of such patterns would indicate that each individual anatomical structure has a unique signature associated with it, thereby allowing for classification of fetal ultrasound clips without directly reading the actual fetal ultrasound images in a convolutional neural network.</p>\",\"PeriodicalId\":94280,\"journal\":{\"name\":\"Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention\",\"volume\":\"15004 \",\"pages\":\"786-795\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7616787/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/978-3-031-72083-3_73\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-031-72083-3_73","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

在胎儿超声波扫描过程中,超声波技师会放大和缩小图像,试图获得更清晰的相关解剖结构图像。本文探讨了如何利用这种缩放信息,因为这种信息可从胎儿超声图像中提取,但未得到充分利用。我们探索将缩放模式与特定结构联系起来。这种模式的存在将表明每个单独的解剖结构都有与之相关的独特特征,从而可以在卷积神经网络中对胎儿超声片段进行分类,而无需直接读取实际的胎儿超声图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Zoom Pattern Signatures for Fetal Ultrasound Structures.

During a fetal ultrasound scan, a sonographer will zoom in and zoom out as they attempt to get clearer images of the anatomical structures of interest. This paper explores how to use this zoom information which is an under-utilised piece of information that is extractable from fetal ultrasound images. We explore associating zooming patterns to specific structures. The presence of such patterns would indicate that each individual anatomical structure has a unique signature associated with it, thereby allowing for classification of fetal ultrasound clips without directly reading the actual fetal ultrasound images in a convolutional neural network.

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
期刊最新文献
Zoom Pattern Signatures for Fetal Ultrasound Structures. Self-guided Knowledge-Injected Graph Neural Network for Alzheimer's Diseases. Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equation. Attention-Enhanced Fusion of Structural and Functional MRI for Analyzing HIV-Associated Asymptomatic Neurocognitive Impairment. Tagged-to-Cine MRI Sequence Synthesis via Light Spatial-Temporal Transformer.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1