A general method for the identification and repair of concavities in segmented medical images

The segmentation of structures of interest in medical images can result in segmentation boundaries demonstrating two types of concavities: natural and incorrect. This study introduces a generalized method for identification and repair of incorrect concavities. Previous methods are framed in terms of the generalized method and new techniques for concavity identification, α -hull, and repair, active contours, are applied. The application of α -hulls also creates a natural hierarchy on concavities that leads to more efficient computations for both the characterization and repair of concavities. The generalized method is evaluated on a database of juxtapleural nodules and compared against two other methods: convex hull and morphological closing operator. The generalized method demonstrates the best overall tradeoff between juxtapleural nodule inclusion and incorrect inclusion of non-nodule tissue from surrounding structures.