您的位置: 首页 > 农业专利 > 详情页

Deep Learning Reconstruction of Free Breathing Perfusion
专利权人:
University of Utah Research Foundation;Siemens Healthcare GmbH
发明人:
Bradley Drake Bolster, JR.,Ganesh Sharma Adluru Venkata Raja,Edward DiBella
申请号:
US15980774
公开号:
US20190353741A1
申请日:
2018.05.16
申请国别(地区):
US
年份:
2019
代理人:
摘要:
A method for reducing artifacts in magnetic resonance imaging (MRI) data includes acquiring a k-space dataset of an anatomical subject using a MRI scanner. An iterative compressed sensing reconstruction method is used to generate a reconstructed image based on the k-space dataset. This iterative compressed sensing reconstruction method uses (a) L1-norm based total variation constraints applied the temporal and spatial dimensions of the k-space dataset and (b) a low rank constraint. After the reconstructed image is generated, a deep learning network is used to generate an artifact image depicting motion artifacts present in the reconstructed image. The reconstructed image is subtracted from the artifact image to yield a final image with the motion artifacts removed.
来源网站:
中国工程科技知识中心
来源网址:
http://www.ckcest.cn/home/
相关发明人
相关专利

意 见 箱

匿名:登录

个人用户登录

找回密码

第三方账号登录

忘记密码

个人用户注册

必须为有效邮箱
6~16位数字与字母组合
6~16位数字与字母组合
请输入正确的手机号码

信息补充