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在最小化金属伪影方面，回波不对称最小二乘估计迭代水脂分解（IDEAL）成像的实际应用。

Practical application of iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) imaging in minimizing metallic artifacts.

机构信息

Department of Radiology, Soonchunhyang University Bucheon Hospital, Bucheon 420-767, Korea.

出版信息

Korean J Radiol. 2012 May-Jun;13(3):332-41. doi: 10.3348/kjr.2012.13.3.332. Epub 2012 Apr 17.

DOI:10.3348/kjr.2012.13.3.332
PMID:22563271
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3337870/
Abstract

Iterative decomposition of water and fat with echo asymmetry and the least-squares estimation (IDEAL) is a recently developed method for robust separation of fat and water with very high signal-to-noise-ratio (SNR) efficiency. In contrast to conventional fat-saturation methods, IDEAL is insensitive to magnetic field (B0 and B1) inhomogeneity. The aim of this study was to illustrate the practical application of the IDEAL technique in reducing metallic artifacts in postoperative patients with metallic hardware. The IDEAL technique can help musculoskeletal radiologists make an accurate diagnosis particularly in musculoskeletal imaging by reducing metallic artifacts, enabling the use of contrast enhancement, improving SNR performance, and providing various modes of MR images with one scan parameter.

摘要

迭代水脂分离反演的最小二乘估计（IDEAL）是一种最近开发的方法，可实现具有非常高信噪比（SNR）效率的脂肪和水的稳健分离。与传统的脂肪饱和方法不同，IDEAL 对磁场（B0 和 B1）不均匀性不敏感。本研究的目的是说明 IDEAL 技术在减少术后有金属植入物的患者的金属伪影方面的实际应用。IDEAL 技术可以帮助肌肉骨骼放射科医生做出准确的诊断，特别是在减少金属伪影的肌肉骨骼成像中，从而能够使用对比增强、提高 SNR 性能，并提供一种扫描参数的多种 MR 图像模式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/31177fe39ffd/kjr-13-332-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/1b76619787b2/kjr-13-332-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/31177fe39ffd/kjr-13-332-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/7d726d91af42/kjr-13-332-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/09c681b0b026/kjr-13-332-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/e8c392185a09/kjr-13-332-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/2211158bd8d9/kjr-13-332-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/0a879283a266/kjr-13-332-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/251fc553f5c2/kjr-13-332-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/4cd9ee3cc7b4/kjr-13-332-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/41c992094233/kjr-13-332-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/b83725190fb1/kjr-13-332-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/b5c3493db43a/kjr-13-332-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/1b76619787b2/kjr-13-332-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29a8/3337870/31177fe39ffd/kjr-13-332-g012.jpg

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