从两张未校准的乳房x线摄影图像中重建血管

M. Babaee, A. R. Naghsh Nilchi
{"title":"从两张未校准的乳房x线摄影图像中重建血管","authors":"M. Babaee, A. R. Naghsh Nilchi","doi":"10.1109/ICBME.2014.7043914","DOIUrl":null,"url":null,"abstract":"Three dimensional modeling of organs plays a crucial role in the treatment of cancer and radio vascular diseases. The purpose of this work is 3D modeling of breast vessels using only two uncalibrated two-dimensional mammography images in order to have the patient less exposed to X-ray radiation. In the proposed method, we first optimize the internal and external parameters using a nonlinear optimization framework. To this end, we use the data stored in the header of files and key features in the mammography images. Using the optimized parameters, 3D active contours is proposed for 3D modeling of the vessels. Then using the parameters obtained from the previous step, an initial active curve gradually evolves until the energy of active curve is minimized. The surface reconstruction of the vessels is done by employing the methods converting a set of surface points to lattice surface. The proposed method is implied for a set of mammography images. Assuming optimized parameters are achieved, the method can yield promising 3D reconstruction.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"3D reconstruction of vessels from two uncalibrated mammography images\",\"authors\":\"M. Babaee, A. R. Naghsh Nilchi\",\"doi\":\"10.1109/ICBME.2014.7043914\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Three dimensional modeling of organs plays a crucial role in the treatment of cancer and radio vascular diseases. The purpose of this work is 3D modeling of breast vessels using only two uncalibrated two-dimensional mammography images in order to have the patient less exposed to X-ray radiation. In the proposed method, we first optimize the internal and external parameters using a nonlinear optimization framework. To this end, we use the data stored in the header of files and key features in the mammography images. Using the optimized parameters, 3D active contours is proposed for 3D modeling of the vessels. Then using the parameters obtained from the previous step, an initial active curve gradually evolves until the energy of active curve is minimized. The surface reconstruction of the vessels is done by employing the methods converting a set of surface points to lattice surface. The proposed method is implied for a set of mammography images. Assuming optimized parameters are achieved, the method can yield promising 3D reconstruction.\",\"PeriodicalId\":434822,\"journal\":{\"name\":\"2014 21th Iranian Conference on Biomedical Engineering (ICBME)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 21th Iranian Conference on Biomedical Engineering (ICBME)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBME.2014.7043914\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBME.2014.7043914","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

器官的三维建模在癌症和放射性血管疾病的治疗中起着至关重要的作用。这项工作的目的是仅使用两张未经校准的二维乳房x线摄影图像对乳腺血管进行3D建模,以便使患者较少暴露于x射线辐射。在该方法中,我们首先使用非线性优化框架对内外参数进行优化。为此,我们使用存储在文件头中的数据和乳房x线摄影图像中的关键特征。利用优化后的参数,提出了用于血管三维建模的三维活动轮廓。然后利用前一步得到的参数,逐渐演化出一条初始活动曲线,直到活动曲线能量最小。采用将一组表面点转换为点阵表面的方法对容器进行表面重建。该方法适用于一组乳房x线摄影图像。在参数得到优化的前提下,该方法可以得到很好的三维重建效果。
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
3D reconstruction of vessels from two uncalibrated mammography images
Three dimensional modeling of organs plays a crucial role in the treatment of cancer and radio vascular diseases. The purpose of this work is 3D modeling of breast vessels using only two uncalibrated two-dimensional mammography images in order to have the patient less exposed to X-ray radiation. In the proposed method, we first optimize the internal and external parameters using a nonlinear optimization framework. To this end, we use the data stored in the header of files and key features in the mammography images. Using the optimized parameters, 3D active contours is proposed for 3D modeling of the vessels. Then using the parameters obtained from the previous step, an initial active curve gradually evolves until the energy of active curve is minimized. The surface reconstruction of the vessels is done by employing the methods converting a set of surface points to lattice surface. The proposed method is implied for a set of mammography images. Assuming optimized parameters are achieved, the method can yield promising 3D reconstruction.
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
A time-delay parallel cascade identification system for predicting jaw movements Automated decomposition of needle EMG signal using STFT and wavelet transforms Sparse representation-based super-resolution for diffusion weighted images Investigation of Brain Default Network's activation in autism spectrum disorders using Group Independent Component Analysis Pragmatic modeling of chaotic dynamical systems through artificial neural network
×
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