The processing and analysis of computed tomography (CT) imaging is important for both basic scientific development and clinical applications. In AutoCT, we provide a comprehensive pipeline that integrates an end-to-end automatic preprocessing, registration, segmentation, and quantitative analysis of 3D CT scans. The engineered pipeline enables atlas-based CT segmentation and quantification leveraging diffeomorphic transformations through efficient forward and inverse mappings. The extracted localized features from the deformation field allow for downstream statistical learning that may facilitate medical diagnostics. On a lightweight and portable software platform, AutoCT provides a new toolkit for the CT imaging community to underpin the deployment of artificial intelligence-driven applications.

翻译：计算机断层扫描（CT）成像的处理与分析对于基础科学发展及临床应用均具有重要意义。在AutoCT中，我们提供了一个综合流程，该流程集成了3D CT扫描的端到端自动预处理、配准、分割及定量分析。所设计的流程通过高效的正向与逆映射利用微分同胚变换，实现了基于图谱的CT分割与量化。从形变场中提取的局部特征可支持下游统计学习，从而辅助医学诊断。基于轻量化且便携的软件平台，AutoCT为CT成像领域提供了一套新型工具包，旨在支撑人工智能驱动应用的实际部署。