کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6032218 1188739 2011 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Parcellation of human amygdala in vivo using ultra high field structural MRI
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
Parcellation of human amygdala in vivo using ultra high field structural MRI
چکیده انگلیسی

Histological studies show that human amygdala is subdivided into several nuclei with specific connections to other brain areas. One such study has been recently used as the basis of a probabilistic amygdala map, to enable in vivo identification of specifically located functions within the amygdala and connections to it. The involvement of the amygdala in cognition, emotion and action, which may underlie several psychiatric disorders, points to a need for discrimination of these nuclei in living human brains using different techniques. Structural MRI scans of the human amygdala at standard field strengths (≤ 3 T) have shown a region of generally featureless gray matter. Apparently homogeneous regions may reveal internal structure, however, when improved imaging strategies and better SNR are available. The goal of this study is the in vivo anatomical segmentation of the amygdala using high resolution structural MR data. The use of different MRI tissue contrast mechanisms at high field strengths has been little explored so far. Combining two different contrasts, and using cutting-edge image analysis, the following study provides a robust clustering of three amygdala components in vivo using 7 T structural imaging.


► The high CNR available at 7 T enables the segmentation of the amygdala in vivo.
► MR contrast combination provides a more precise tissue segmentation.
► Spectral clustering provided three sets of robustly distinguishable areas on structural images.
► Consistency is checked across subjects, coils used and image intensities.
► These segments have been compared to previous in vivo and ex vivo amygdala maps.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 58, Issue 3, 1 October 2011, Pages 741–748