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首页> 外文期刊>Journal of Neuroscience Methods >Adaptive prior probability and spatial temporal intensity change estimation for segmentation of the one-year-old human brain.
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Adaptive prior probability and spatial temporal intensity change estimation for segmentation of the one-year-old human brain.

机译：单岁人脑分割的自适应现有概率和空间时间强度变化估计。

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The degree of white matter (WM) myelination is rather inhomogeneous across the brain. White matter appears differently across the cortical lobes in MR images acquired during early postnatal development. Specifically at 1-year of age, the gray/white matter contrast of MR T1 and T2 weighted images in prefrontal and temporal lobes is reduced as compared to the rest of the brain, and thus, tissue segmentation results commonly show lower accuracy in these lobes. In this novel work, we propose the use of spatial intensity growth maps (IGM) for T1 and T2 weighted images to compensate for local appearance inhomogeneity. The IGM captures expected intensity changes from 1 to 2years of age, as appearance homogeneity is greatly improved by the age of 24months. The IGM was computed as the coefficient of a voxel-wise linear regression model between corresponding intensities at 1 and 2years. The proposed IGM method revealed low regression values of 1-10% in GM and CSF regions, as well as in WM regions at maturation stage of myelination at 1year. However, in the prefrontal and temporal lobes we observed regression values of 20-25%, indicating that the IGM appropriately captures the expected large intensity change in these lobes mainly due to myelination. The IGM is applied to cross-sectional MRI datasets of 1-year-old subjects via registration, correction and tissue segmentation of the IGM-corrected dataset. We validated our approach in a small leave-one-out study of images with known, manual 'ground truth' segmentations.
机译：白质（wm）髓鞘中的程度相当不均匀。在早期产后于产后期间获得的MR图像中，白质在皮质裂片中出现不同。特别是在1年龄，与脑部的其余部分相比，预先平整和颞叶MR T1和T2加权图像的灰色/白质对比，因此，组织分割结果通常在这些叶片中较低的准确度。在这部小型工作中，我们提出了使用用于T1和T2加权图像的空间强度生长图（IGM）以补偿局部外观的不均匀性。 IGM捕获预期的强度从1到2年的年龄变化，因为外观均匀性大大提高到24个月。将IgM计算为在1和2年的相应强度之间的体素-WIES线性回归模型的系数。所提出的IgM方法显示出GM和CSF地区1-10％的低回归值，以及1年在髓鞘中成熟阶段的WM区。然而，在前额和颞叶中，我们观察到20-25％的回归值，表明IgM适当地捕获这些裂片中的预期大强度变化主要是由于髓鞘导致的这些裂片。通过注册，校正和组织分割，将IgM应用于1岁科目的横截面MRI数据集，通过IGM校正的数据集进行了登记，校正和组织分割。我们验证了我们的方法，在一个小的休假研究中，通过已知的手动“实际”分割。

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