Subtle pitfalls in the search for faster medical imaging.
作者信息
Block Kai Tobias
机构信息
Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), New York University Grossman School of Medicine, New York, NY 10016.
出版信息
Proc Natl Acad Sci U S A. 2022 Apr 26;119(17):e2203040119. doi: 10.1073/pnas.2203040119. Epub 2022 Apr 22.
Abstract
摘要
相似文献
1
Subtle pitfalls in the search for faster medical imaging.追求更快医学成像中的细微陷阱。
Proc Natl Acad Sci U S A. 2022 Apr 26;119(17):e2203040119. doi: 10.1073/pnas.2203040119. Epub 2022 Apr 22.
2
Pitfalls in Liver Imaging.肝脏影像学中的陷阱。
Radiology. 2016 Jan;278(1):34-51. doi: 10.1148/radiol.2015142576.
3
Imaging characteristics of a Stafne bone cavity--panoramic radiography, computed tomography and magnetic resonance imaging.斯丹氏骨腔的影像学特征——全景X线摄影、计算机断层扫描和磁共振成像
Oral Maxillofac Surg. 2014 Sep;18(3):351-3. doi: 10.1007/s10006-014-0454-5. Epub 2014 Aug 7.
4
Orbital Implants: Normal Imaging Appearance, Pitfalls and Complications.眼眶植入物：正常影像学表现、陷阱与并发症
Semin Roentgenol. 2019 Jul;54(3):227-243. doi: 10.1053/j.ro.2019.03.004. Epub 2019 Mar 6.
5
Imaging for Nonarthritic Hip Pathology.非关节炎性髋关节病变的影像学检查
Am J Orthop (Belle Mead NJ). 2017 Jan/Feb;46(1):17-22.
6
The Great Mimickers of Spinal Pathology.脊柱病理学中的大“伪装者”。
Semin Musculoskelet Radiol. 2022 Aug;26(4):439-452. doi: 10.1055/s-0042-1748914. Epub 2022 Sep 14.
7
Pitfalls in paediatric oncology imaging.儿科肿瘤影像学中的陷阱。
Cancer Imaging. 2011 Sep 24;11(1):144-54. doi: 10.1102/1470-7330.2011.0021.
8
Pearls and Pitfalls in Neck Imaging.颈部影像学的要点与陷阱
Neuroimaging Clin N Am. 2022 May;32(2):375-390. doi: 10.1016/j.nic.2022.02.002.
9
[Computed tomography--magnetic resonance tomography, what and when?].[计算机断层扫描——磁共振断层扫描，是什么以及何时使用？]
Rev Med Suisse. 2015 Jan 28;11(459):302-3.
10
Scanning the scans: comparing CT, MRI, and PET scans.扫描影像：比较CT、MRI和PET扫描
Harv Mens Health Watch. 2004 Jul;8(12):3-6.
引用本文的文献
1
Ten quick tips for computational analysis of medical images.医学图像计算分析的十个快速技巧。
PLoS Comput Biol. 2023 Jan 5;19(1):e1010778. doi: 10.1371/journal.pcbi.1010778. eCollection 2023 Jan.
本文引用的文献
1
Implicit data crimes: Machine learning bias arising from misuse of public data.隐性数据犯罪：因公共数据滥用导致的机器学习偏差
Proc Natl Acad Sci U S A. 2022 Mar 29;119(13):e2117203119. doi: 10.1073/pnas.2117203119. Epub 2022 Mar 21.
2
fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning.快速磁共振成像（fastMRI）：一个公开可用的膝关节图像原始k空间和DICOM数据集，用于使用机器学习加速磁共振图像重建。
Radiol Artif Intell. 2020 Jan 29;2(1):e190007. doi: 10.1148/ryai.2020190007.
3
Learning a variational network for reconstruction of accelerated MRI data.学习用于加速 MRI 数据重建的变分网络。
Magn Reson Med. 2018 Jun;79(6):3055-3071. doi: 10.1002/mrm.26977. Epub 2017 Nov 8.
4
Bloch-based MRI system simulator considering realistic electromagnetic fields for calculation of signal, noise, and specific absorption rate.基于布洛赫方程的磁共振成像系统模拟器，考虑实际电磁场用于计算信号、噪声和比吸收率。
Magn Reson Med. 2014 Jul;72(1):237-47. doi: 10.1002/mrm.24907. Epub 2013 Sep 4.
5
Sparse MRI: The application of compressed sensing for rapid MR imaging.稀疏磁共振成像：压缩感知在快速磁共振成像中的应用。
Magn Reson Med. 2007 Dec;58(6):1182-95. doi: 10.1002/mrm.21391.
6
Image formation by induced local interactions. Examples employing nuclear magnetic resonance. 1973.通过诱导局部相互作用形成图像。核磁共振示例。1973年。
Clin Orthop Relat Res. 1989 Jul(244):3-6.
Zotero 插件