避免纵向图像处理中的不对称诱导偏差。
Avoiding asymmetry-induced bias in longitudinal image processing.
机构信息
Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA; MIT Computer Science and AI Lab, Cambridge, MA, USA.
出版信息
Neuroimage. 2011 Jul 1;57(1):19-21. doi: 10.1016/j.neuroimage.2011.02.076. Epub 2011 Mar 3.
Abstract
Longitudinal image processing procedures frequently transfer or pool information across time within subject, with the dual goals of reducing the variability and increasing the accuracy of the derived measures. In this note, we discuss common difficulties in longitudinal image processing, focusing on the introduction of bias, and describe the approaches we have taken to avoid them in the FreeSurfer longitudinal processing stream.
摘要
纵向图像处理程序经常在受试者内跨时间转移或汇集信息，其双重目标是降低所得测量值的变异性和提高准确性。在本说明中，我们讨论了纵向图像处理中的常见困难，重点介绍了引入偏差的问题，并描述了我们在 FreeSurfer 纵向处理流程中避免这些问题的方法。
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