کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6036124 | 1188773 | 2010 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Unsupervised white matter fiber clustering and tract probability map generation: Applications of a Gaussian process framework for white matter fibers
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
This article presents such a novel mathematical framework that facilitates mathematical operations between tracts using an inner product between fibres. Such inner product operation, based on Gaussian processes, spans a metric space. This metric facilitates combination of fiber tracts, rendering operations like tract membership to a bundle or bundle similarity simple. Based on this framework, we have designed an automated unsupervised atlas-based clustering method that does not require manual initialization nor an a priori knowledge of the number of clusters. Quantitative analysis can now be performed on the clustered tract volumes across subjects, thereby avoiding the need for point parameterization of these fibers, or the use of medial or envelope representations as in previous work. Experiments on synthetic data demonstrate the mathematical operations. Subsequently, the applicability of the unsupervised clustering framework has been demonstrated on a 21-subject dataset.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 51, Issue 1, 15 May 2010, Pages 228-241
Journal: NeuroImage - Volume 51, Issue 1, 15 May 2010, Pages 228-241
نویسندگان
D. Wassermann, L. Bloy, E. Kanterakis, R. Verma, R. Deriche,