کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6026128 1188677 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multi-label segmentation of white matter structures: Application to neonatal brains
ترجمه فارسی عنوان
تقسیم بندی چند لایه ساختارهای ماده سفید: کاربرد در مغز نوزادان
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
چکیده انگلیسی


- A supervised multi-label white matter segmentation method is developed.
- Multiple labels of white matter tracts were assigned to each location.
- 13 white matter tracts were automatically delineated from the neonatal brain.

Accurate and consistent segmentation of brain white matter bundles at neonatal stage plays an important role in understanding brain development and detecting white matter abnormalities for the prediction of psychiatric disorders. Due to the complexity of white matter anatomy and the spatial resolution of diffusion-weighted MR imaging, multiple fiber bundles can pass through one voxel. The goal of this study is to assign one or multiple anatomical labels of white matter bundles to each voxel to reflect complex white matter anatomy of the neonatal brain. For this, we develop a supervised multi-label k-nearest neighbor (ML-kNN) classification algorithm in Riemannian diffusion tensor spaces. Our ML-kNN considers diffusion tensors lying on the Log-Euclidean Riemannian manifold of symmetric positive definite (SPD) matrices and their corresponding vector space as feature space. The ML-kNN utilizes the maximum a posteriori (MAP) principle to make the prediction of white matter labels by reasoning with the labeling information derived from the neighbors without assuming any probabilistic distribution of the features. We show that our approach automatically learns the number of white matter bundles at a location and provides anatomical annotation of the neonatal white matter. In addition, our approach also provides the binary mask for individual white matter bundles to facilitate tract-based statistical analysis in clinical studies. We apply this method to automatically segment 13 white matter bundles of the neonatal brain and examine the segmentation accuracy against semi-manual labels derived from tractography.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 102, Part 2, 15 November 2014, Pages 913-922
نویسندگان
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