کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4637683 1631978 2017 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Tomographic image reconstruction using training images
ترجمه فارسی عنوان
بازسازی تصویر توموگرافی با استفاده از تصاویر آموزشی
کلمات کلیدی
توموگرافی؛ یادگیری واژه نامه. مشکلات معکوس؛ منظم سازی؛ بازنمایی انحصاری؛ بازسازی تصویر
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات ریاضیات کاربردی
چکیده انگلیسی

We describe and examine an algorithm for tomographic image reconstruction where prior knowledge about the solution is available in the form of training images. We first construct a non-negative dictionary based on prototype elements from the training images; this problem is formulated within the framework of sparse learning as a regularized non-negative matrix factorization. Incorporating the dictionary as a prior in a convex reconstruction problem, we then find an approximate solution with a sparse representation in the dictionary. The dictionary is applied to non-overlapping patches of the image, which reduces the computational complexity compared to previous formulations. Computational experiments clarify the choice and interplay of the model parameters and the regularization parameters, and we show that in few-projection low-dose settings our algorithm is competitive with total variation regularization and tends to include more texture and more correct edges.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Computational and Applied Mathematics - Volume 313, 15 March 2017, Pages 243–258
نویسندگان
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