کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6028120 1580921 2013 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Collaborative patch-based super-resolution for diffusion-weighted images
ترجمه فارسی عنوان
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موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
چکیده انگلیسی


- Introduction of a new collaborative patch-based super-resolution method for DWI
- Extensive validation of image reconstruction quality on real DWI images
- Investigation of the impact of our method on diffusion parameter, tensor and q-ball
- Presentation of results of ultrahigh resolution DWI with fiber tracking examples

In this paper, a new single image acquisition super-resolution method is proposed to increase image resolution of diffusion weighted (DW) images. Based on a nonlocal patch-based strategy, the proposed method uses a non-diffusion image (b0) to constrain the reconstruction of DW images. An extensive validation is presented with a gold standard built on averaging 10 high-resolution DW acquisitions. A comparison with classical interpolation methods such as trilinear and B-spline demonstrates the competitive results of our proposed approach in terms of improvements on image reconstruction, fractional anisotropy (FA) estimation, generalized FA and angular reconstruction for tensor and high angular resolution diffusion imaging (HARDI) models. Besides, first results of reconstructed ultra high resolution DW images are presented at 0.6 × 0.6 × 0.6 mm3 and 0.4 × 0.4 × 0.4 mm3 using our gold standard based on the average of 10 acquisitions, and on a single acquisition. Finally, fiber tracking results show the potential of the proposed super-resolution approach to accurately analyze white matter brain architecture.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 83, December 2013, Pages 245-261
نویسندگان
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