Segmenting the inner cavity regions of precision parts from industrial CT images is crucial for accurate dimensional measurements. However, inner cavities are often non-closed and exhibit CT grayscale values similar to the background, making accurate segmentation challenging for existing algorithms. To address this, this paper introduces a local multi-scale convex hull algorithm that integrates convex hull concepts with mathematical morphology. Starting from an initial segmentation, the algorithm fills the inner cavity regions, followed by closing and Boolean operations to achieve complete segmentation. Comparative experiments with various segmentation methods demonstrate the effectiveness of the proposed approach, achieving an F1 score of 0. 973 5 on CT images of automotive parts. The results indicate that the proposed algorithm offers high accuracy and efficiency, enabling the precise and rapid segmentation of non-closed inner cavity regions in diverse industrial CT image applications.