Cryo-electron tomography (cryo-ET) enables high resolution, three-dimensional reconstruction of biological structures, including membranes and membrane proteins. Identification of regions of interest (ROIs) is central to scientific imaging, as it enables isolation and quantitative analysis of specific structural features within complex datasets. In practice, however, ROIs are typically derived indirectly through full structure segmentation followed by post hoc analysis. This limitation is especially apparent for continuous and geometrically complex structures such as membranes, which are segmented as single entities. Here, we developed TomoROIS-SurfORA, a two step framework for direct, shape-agnostic ROI segmentation and morphological surface analysis. TomoROIS performs deep learning-based ROI segmentation and can be trained from scratch using small annotated datasets, enabling practical application across diverse imaging data. SurfORA processes segmented structures as point clouds and surface meshes to extract quantitative morphological features, including inter-membrane distances, curvature, and surface roughness. It supports both closed and open surfaces, with specific considerations for open surfaces, which are common in cryo-ET due to the missing wedge effect. We demonstrate both tools using in vitro reconstituted membrane systems containing deformable vesicles with complex geometries, enabling automatic quantitative analysis of membrane contact sites and remodeling events such as invagination. While demonstrated here on cryo-ET membrane data, the combined approach is applicable to ROI detection and surface analysis in broader scientific imaging contexts.

翻译：冷冻电子断层扫描（cryo-ET）能够实现包括膜及膜蛋白在内的生物结构的高分辨率三维重建。感兴趣区域（ROI）的识别是科学成像的核心环节，因为它能够从复杂数据集中分离出特定结构特征并进行定量分析。然而在实践中，ROI通常需通过全结构分割及后续分析间接获得。这一局限对于膜等连续且几何结构复杂的对象尤为明显——它们通常被分割为单一实体。本研究开发了TomoROIS-SurfORA框架，该两步式框架可直接进行与形状无关的ROI分割及形态学表面分析。TomoROIS基于深度学习实现ROI分割，仅需少量标注数据即可从头训练，适用于多样化的成像数据。SurfORA将分割结构处理为点云与表面网格，以提取包括膜间距、曲率和表面粗糙度在内的定量形态特征。该工具支持封闭与开放表面，并针对冷冻电子断层扫描中因缺失楔效应常见的开放表面进行了专门设计。我们通过包含复杂几何形变囊泡的体外重构膜系统验证了这两个工具，实现了对膜接触位点及内陷等重塑事件的自动定量分析。虽然本文以冷冻电子断层扫描膜数据为例，该组合方法可广泛应用于更广泛科学成像场景中的ROI检测与表面分析。