Research on the Application of Deep Learning in Human Spinal Image Segmentation

Zhao Feng, Qi Min, Xu Hua
{"title":"Research on the Application of Deep Learning in Human Spinal Image Segmentation","authors":"Zhao Feng, Qi Min, Xu Hua","doi":"10.1088/1742-6596/2833/1/012011","DOIUrl":null,"url":null,"abstract":"Traditional segmentation methods can only segment grayscale images, which limits their application; The segmentation process often depends on the doctor’s experience, which can lead to subjective factors affecting the results; Therefore, the accuracy and efficiency of segmentation are difficult to achieve practical application results. The deep learning model is a structural model that mimics the neural connections within the human brain. The deep learning model can accurately extract multi-level features of key information in images from low-level to high-level, and provide feedback on data interpretation, thereby achieving accurate and efficient image segmentation results. Introducing deep learning algorithms into medical image segmentation can accurately express the key information at a deeper level in spinal images, achieving better image segmentation results.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Physics: Conference Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/1742-6596/2833/1/012011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Traditional segmentation methods can only segment grayscale images, which limits their application; The segmentation process often depends on the doctor’s experience, which can lead to subjective factors affecting the results; Therefore, the accuracy and efficiency of segmentation are difficult to achieve practical application results. The deep learning model is a structural model that mimics the neural connections within the human brain. The deep learning model can accurately extract multi-level features of key information in images from low-level to high-level, and provide feedback on data interpretation, thereby achieving accurate and efficient image segmentation results. Introducing deep learning algorithms into medical image segmentation can accurately express the key information at a deeper level in spinal images, achieving better image segmentation results.
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
深度学习在人体脊柱图像分割中的应用研究
传统的分割方法只能分割灰度图像,限制了其应用范围;分割过程往往依赖医生的经验,会导致主观因素影响分割结果;因此,分割的准确性和效率难以达到实际应用效果。深度学习模型是一种模仿人脑神经连接的结构模型。深度学习模型可以准确提取图像中关键信息从低级到高级的多层次特征,并对数据解读进行反馈,从而实现准确高效的图像分割结果。将深度学习算法引入医学影像分割,可以准确表达脊柱图像中更深层次的关键信息,实现更好的图像分割效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
1.20
自引率
0.00%
发文量
0
期刊最新文献
Research and design of low-noise cooling fan for fuel cell vehicle Enhanced heat transfer technology for solar air heaters Comparison of thermo-catalytic and photo-assisted thermo-catalytic conversion of glucose to HMF with Cr-MOFs@ZrO2 Mechanical integrity analysis of caprock during the CO2 injection phase Numerical study of film cooling at the outlet of gas turbine exhaust
×
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