Fully automated planning for anatomical fetal brain MRI on 0.55T

Author:

Neves Silva Sara12ORCID,McElroy Sarah13ORCID,Aviles Verdera Jordina12ORCID,Colford Kathleen12,St Clair Kamilah12,Tomi‐Tricot Raphael13,Uus Alena12ORCID,Ozenne Valéry4,Hall Megan25,Story Lisa25,Pushparajah Kuberan2,Rutherford Mary A.12,Hajnal Joseph V.12,Hutter Jana126ORCID

Affiliation:

1. Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences King's College London London UK

2. Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences King's College London London UK

3. MR Research Collaborations Siemens Healthcare Limited Camberley UK

4. CNRS, CRMSB, UMR 5536, IHU Liryc Université de Bordeaux Bordeaux France

5. Department of Women & Children's Health King's College London London UK

6. Smart Imaging Lab, Radiological Institute Friedrich‐Alexander University Erlangen‐Nuremberg Erlangen Germany

Abstract

AbstractPurposeWidening the availability of fetal MRI with fully automatic real‐time planning of radiological brain planes on 0.55T MRI.MethodsDeep learning‐based detection of key brain landmarks on a whole‐uterus echo planar imaging scan enables the subsequent fully automatic planning of the radiological single‐shot Turbo Spin Echo acquisitions. The landmark detection pipeline was trained on over 120 datasets from varying field strength, echo times, and resolutions and quantitatively evaluated. The entire automatic planning solution was tested prospectively in nine fetal subjects between 20 and 37 weeks. A comprehensive evaluation of all steps, the distance between manual and automatic landmarks, the planning quality, and the resulting image quality was conducted.ResultsProspective automatic planning was performed in real‐time without latency in all subjects. The landmark detection accuracy was 4.2 2.6 mm for the fetal eyes and 6.5 3.2 for the cerebellum, planning quality was 2.4/3 (compared to 2.6/3 for manual planning) and diagnostic image quality was 2.2 compared to 2.1 for manual planning.ConclusionsReal‐time automatic planning of all three key fetal brain planes was successfully achieved and will pave the way toward simplifying the acquisition of fetal MRI thereby widening the availability of this modality in nonspecialist centers.

Funder

Deutsche Forschungsgemeinschaft

Health Services and Delivery Research Programme

UK Research and Innovation

Wellcome EPSRC Centre for Medical Engineering

Publisher

Wiley

同舟云学术

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