论文标题
用于神经影像学数据分析的统计学习方法
Statistical learning methods for neuroimaging data analysis with applications
论文作者
论文摘要
本文的目的是对从神经成像技术到大规模神经影像学研究再到统计学习方法的神经影像学分析中的统计挑战进行全面综述。我们简要回顾了八种流行的神经影像学技术及其在神经科学研究和临床翻译中的潜在应用。我们描述了神经影像数据的四个常见主题，并回顾了用于处理单个级别的神经成像数据的主要图像处理分析方法。我们简要回顾了四个大规模神经成像研究和成像基因组学的联盟，并在人群水平上讨论了神经成像数据分析的四个常见主题。我们回顾了九种主要的基于人群的统计分析方法及其相关的统计挑战，并在统计方法论上呈现了解决这些挑战的最新进展。
The aim of this paper is to provide a comprehensive review of statistical challenges in neuroimaging data analysis from neuroimaging techniques to large-scale neuroimaging studies to statistical learning methods. We briefly review eight popular neuroimaging techniques and their potential applications in neuroscience research and clinical translation. We delineate the four common themes of neuroimaging data and review major image processing analysis methods for processing neuroimaging data at the individual level. We briefly review four large-scale neuroimaging-related studies and a consortium on imaging genomics and discuss four common themes of neuroimaging data analysis at the population level. We review nine major population-based statistical analysis methods and their associated statistical challenges and present recent progress in statistical methodology to address these challenges.
