We thank all the discussants for sharing their valuable viewpoints on the proposed statistical disease mapping (SDM) framework. In our article, we addressed the issue of imaging heterogeneity at both the global and local scales by efficiently borrowing common information shared among a large number of diseased and normal subjects. Understanding such imaging heterogeneity is critical in the development of urgently needed analytic approaches to the prevention, diagnosis, treatment, and prognosis of many diseases (e.g., Alzheimer's disease, brain cancer, and lung cancer), as well as precision medicine broadly. The discussants emphasized improvements to disease mapping by introducing some alternative modelling strategies and many possible future directions in this research topic. The sections of this rejoinder are organized by discussant to address each of their comments separately.

中文翻译：

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Rejoinder：“用于异类神经影像研究的统计疾病图谱”

我们感谢所有讨论者在提议的统计疾病图谱（SDM）框架上分享他们的宝贵观点。在我们的文章中，我们通过有效地借用在许多患病和正常受试者之间共享的公共信息，解决了全球和本地范围的成像异质性问题。了解这种成像异质性对于开发急需的分析方法以预防，诊断，治疗和预后许多疾病（例如，阿尔茨海默氏病，脑癌和肺癌）以及广泛的精密医学至关重要。讨论者通过在本研究主题中介绍一些替代的建模策略和许多可能的未来方向，强调了对疾病作图的改进。