On 3D differential operators for detecting point landmarks

摘要

Point-based registration of volume image data heavily relies on the selection of suitable landmarks. In this contribution, we study the extraction of 3D point landmarks from images. Point landmarks have a unique position which can be deduced from the intensity variations in a sufficiently large neighborhood around the prominent point. We propose four 3D differential operators which are generalizations of existing 2D operators for detecting points of high intensity variations.