A hole filling algorithm for medical imaging

Surface integrity of 3D medical imaging is crucial for surgery simulation or virtual diagnoses. However, undesirable holes often exist due to external damage on bodies or accessibility limitation on scanners. To bridge the gap, the paper proposes an algorithm of filling holes for 3D medical image data based on moving least squares (MLS) method. In the algorithm, medical data is classified into two types and procedure is designed according to the classification. The procedure consists of two steps, namely hole detection and hole completion. In completion part, the detected hole can be automatically filled by interpolation with known surrounding points. Moreover, a threshold is used to constrain the density of the completed surface, so the sampling rate on reconstructed area complies with the original data. We test our algorithm on two types of medical data and the results indicate a robust solution.