کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10712520 | 1025199 | 2014 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fast multi-contrast MRI reconstruction
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک ماده چگال
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Multi-contrast magnetic resonance imaging (MRI) is a useful technique to aid clinical diagnosis. This paper proposes an efficient algorithm to jointly reconstruct multiple T1/T2-weighted images of the same anatomical cross section from partially sampled k-space data. The joint reconstruction problem is formulated as minimizing a linear combination of three terms, corresponding to a least squares data fitting, joint total variation (TV) and group wavelet-sparsity regularization. It is rooted in two observations: 1) the variance of image gradients should be similar for the same spatial position across multiple contrasts; 2) the wavelet coefficients of all images from the same anatomical cross section should have similar sparse modes. To efficiently solve this problem, we decompose it into joint TV regularization and group sparsity subproblems, respectively. Finally, the reconstructed image is obtained from the weighted average of solutions from the two subproblems, in an iterative framework. Experiments demonstrate the efficiency and effectiveness of the proposed method compared to existing multi-contrast MRI methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Magnetic Resonance Imaging - Volume 32, Issue 10, December 2014, Pages 1344-1352
Journal: Magnetic Resonance Imaging - Volume 32, Issue 10, December 2014, Pages 1344-1352
نویسندگان
Junzhou Huang, Chen Chen, Leon Axel,