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加速化学转移编码心血管磁共振成像,使用分辨率增强网络
Manuel A Morales1, Scott Johnson1, Patrick Pierce1
1Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
概括
一种新的深度学习方法,FastCSE,加速了心血管磁共振化学转移编码 (CSE) 用于心肌脂肪成像. 这种技术可以减少喘息,而不会影响脂肪可视化质量.
科学领域:
- 心血管磁共振 (CMR) 是一种心血管磁共振技术.
- 医疗成像医学成像
- 医疗保健中的人工智能
背景情况:
- 心血管磁共振 (CMR) 化学转移编码 (CSE) 对心肌脂肪成像至关重要.
- 加快CSE获取对于提高患者舒适度和扫描效率至关重要.
研究的目的:
- 开发和评估一个深度学习网络,FastCSE,以加速CSE成像.
- 通过使用一种新的深度学习方法,提高图像清晰度并减少CSE扫描中的工件.
主要方法:
- 快速CSE使用超分辨率生成对抗网络进行复杂值的图像增强.
- 该网络在1519名患者的大数据集上接受了培训,并进行了前性验证.
- 双回声CSE图像以各种分辨率获取,并使用FastCSE处理以恢复清晰度.
主要成果:
- FastCSE成功地在线重建了CSE图像,显著减少了喘息的数量.
- 与标准GRAPPA相比,在FastCSE处理的图像中,图像的清晰度得到了改善,并且响声的工件减少了.
- 在FastCSE图像中的模糊性与更高分辨率,非加速扫描相提并论.
结论:
- 深度学习加速的CSE (FastCSE) 在CMR心肌脂肪成像中有效地减少了喘息.
- 该技术保持图像质量和清晰度,为心血管成像提供了有前途的进步.
- 在FastCSE中,图像的清晰度与标准化的并行成像方法相提并论.
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