کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1806102 | 1399657 | 2016 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Optimizing the ICE decoupling element distance to improve monopole antenna arrays for 7 Tesla MRI
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک ماده چگال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Optimizing the ICE decoupling element distance to improve monopole antenna arrays for 7 Tesla MRI Optimizing the ICE decoupling element distance to improve monopole antenna arrays for 7 Tesla MRI](/preview/png/1806102.png)
چکیده انگلیسی
The induced current elimination (ICE) method has been previously applied to decouple monopole coil arrays in ultrahigh field MRI. However, the method creates low B1+ spots near the decoupling elements. In this study, we aim to improve the performance of ICE-decoupled monopole array in human head imaging at 7 Tesla. Eight-channel ICE-decoupled monopole arrays were optimized by varying the position of the decoupling elements. A series of numerical studies were performed using the co-simulation method. In simulation, decoupling performance, quality (Q-) values and transmit field (B1+) were comparatively investigated. In addition, we constructed an optimized ICE-decoupled monopole array and compared its performance with the unoptimized array. The simulation results showed that a good trade-off between decoupling and B1+ loss can be obtained when decoupling elements were moved 2.5-cm away from coil elements. This was validated by in-vivo MR imaging using the constructed array. Compared with the unoptimized ICE decoupled monopole array, the optimized array had a more homogeneous transmit field and no dark spots or signal cancellations in the MR images.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Magnetic Resonance Imaging - Volume 34, Issue 9, November 2016, Pages 1264-1268
Journal: Magnetic Resonance Imaging - Volume 34, Issue 9, November 2016, Pages 1264-1268
نویسندگان
Xinqiang Yan, Xiaoliang Zhang, Rong Xue, John C. Gore, William A. Grissom,