تقرير
Sequence adaptive field-imperfection estimation (SAFE): retrospective estimation and correction of $B_1^+$ and $B_0$ inhomogeneities for enhanced MRF quantification
العنوان: | Sequence adaptive field-imperfection estimation (SAFE): retrospective estimation and correction of $B_1^+$ and $B_0$ inhomogeneities for enhanced MRF quantification |
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المؤلفون: | Gao, Mengze, Cao, Xiaozhi, Abraham, Daniel, Zhou, Zihan, Setsompop, Kawin |
سنة النشر: | 2023 |
المجموعة: | Computer Science Physics (Other) |
مصطلحات موضوعية: | Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning, Physics - Medical Physics |
الوصف: | $B_1^+$ and $B_0$ field-inhomogeneities can significantly reduce accuracy and robustness of MRF's quantitative parameter estimates. Additional $B_1^+$ and $B_0$ calibration scans can mitigate this but add scan time and cannot be applied retrospectively to previously collected data. Here, we proposed a calibration-free sequence-adaptive deep-learning framework, to estimate and correct for $B_1^+$ and $B_0$ effects of any MRF sequence. We demonstrate its capability on arbitrary MRF sequences at 3T, where no training data were previously obtained. Such approach can be applied to any previously-acquired and future MRF-scans. The flexibility in directly applying this framework to other quantitative sequences is also highlighted. Comment: 12 pages, 5 figures, submitted to International Society for Magnetic Resonance in Medicine 31th Scientific Meeting, 2024 |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2312.09488 |
رقم الأكسشن: | edsarx.2312.09488 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |