基于高斯平均的DTI脑模板构建方法
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邓岚,王远军
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DTI Brain Template Construction Based on Gaussian Averaging
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Lan DENG,Yuan-jun WANG
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表1 通过高斯FA模板和线性FA模板进行空间标准化前后的FA图之间的关联性(corrFA值)
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Table 1 Correlation of FA maps (corrFA) before and after spatial normalization by Gaussian FA template and linear FA template, respectively
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被试编号 | linear | Gauss | 1 | 0.568 | 0.733 | 2 | 0.643 | 0.664 | 3 | 0.620 | 0.667 | 4 | 0.627 | 0.674 | 5 | 0.605 | 0.684 | 6 | 0.610 | 0.630 | 7 | 0.674 | 0.627 | 8 | 0.606 | 0.708 | 9 | 0.608 | 0.710 | 10 | 0.639 | 0.669 | 11 | 0.629 | 0.690 | 12 | 0.607 | 0.639 | 13 | 0.618 | 0.634 | 14 | 0.652 | 0.659 | 15 | 0.608 | 0.620 | 16 | 0.641 | 0.689 | 17 | 0.674 | 0.675 | 18 | 0.604 | 0.618 | 19 | 0.637 | 0.668 | 20 | 0.591 | 0.605 | 21 | 0.659 | 0.733 | 22 | 0.624 | 0.629 | 23 | 0.631 | 0.632 | 24 | 0.630 | 0.687 | 25 | 0.645 | 0.647 | 26 | 0.677 | 0.712 | 27 | 0.597 | 0.659 | 28 | 0.669 | 0.692 | 29 | 0.653 | 0.662 | 30 | 0.610 | 0.683 | 31 | 0.638 | 0.685 | 32 | 0.627 | 0.675 | 33 | 0.613 | 0.661 | 34 | 0.607 | 0.671 | 35 | 0.627 | 0.652 | 36 | 0.616 | 0.634 | 37 | 0.667 | 0.669 | 38 | 0.604 | 0.688 | 39 | 0.607 | 0.616 | 40 | 0.633 | 0.636 | 41 | 0.679 | 0.685 | 42 | 0.626 | 0.690 | 43 | 0.688 | 0.690 | 44 | 0.608 | 0.637 | 45 | 0.653 | 0.657 | 46 | 0.628 | 0.651 | 47 | 0.693 | 0.698 | 48 | 0.698 | 0.760 | 49 | 0.683 | 0.698 | 50 | 0.664 | 0.719 | 51 | 0.619 | 0.650 | 52 | 0.669 | 0.689 | 53 | 0.607 | 0.608 | 54 | 0.627 | 0.653 | 55 | 0.682 | 0.696 | 平均值±标准差 | 0.635±0.030 | 0.668±0.033 |
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