Self-supervised Recurrent Neural Network for 4D Abdominal and In-utero MR Imaging
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-33843-5_2
Reference16 articles.
1. Lloyd, D.F.A., et al.: Three-dimensional visualisation of the fetal heart using prenatal MRI with motion corrected slice-volume registration. Lancet 393, 1619–1627 (2018)
2. Story, L., Zhang, T., Aljabar, P., Hajnal, J., Shennan, A., Rutherford, M.: Magnetic resonance imaging assessment of lung volumes in fetuses at high risk of preterm birth. BJOG Int. J. Obstet. Gynaecol. 124, 24 (2017)
3. Story, L., Hutter, J., Zhang, T., Shennan, A.H., Rutherford, M.: The use of antenatal fetal magnetic resonance imaging in the assessment of patients at high risk of preterm birth. Eur. J. Obstet. Gynecol. Reprod. Biol. 222, 134–141 (2018)
4. Story, L., et al.: Magnetic resonance imaging assessment of lung: body volume ratios in fetuses at high risk of preterm birth. BJOG Int. J. Obstet. Gynaecol. 126, 8 (2019)
5. Gholipour, A., Estroff, J.A., Warfield, S.K.: Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI. IEEE Trans. Med. Imaging 29(10), 1739–1758 (2010)
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Stop moving: MR motion correction as an opportunity for artificial intelligence;Magnetic Resonance Materials in Physics, Biology and Medicine;2024-02-22
2. OpenMedIA: Open-Source Medical Image Analysis Toolbox and Benchmark Under Heterogeneous AI Computing Platforms;Pattern Recognition and Computer Vision;2022
3. Review and Prospect: Artificial Intelligence in Advanced Medical Imaging;Frontiers in Radiology;2021-12-13
4. Current status of deep learning in abdominal image reconstruction;Artificial Intelligence in Medical Imaging;2021-08-28
5. Deep learning for fast MR imaging: A review for learning reconstruction from incomplete k-space data;Biomedical Signal Processing and Control;2021-07
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3