Thickness estimation of discrete objects is often a critical step for shape analysis and quantification in medical applications. In this paper, we propose an approach to estimate the thickness (diameter or cross-section area) of discrete tree-like tubular objects in 3D binary images. The estimation is performed by an iterative process involving skeletonization, skeleton simplification, discrete cross-section plane eval- uation and finally area estimation. The method is essentially based on discrete geometry concepts (skeleton, discrete planes, and discrete area). It has been validated on phantoms in order to determine its robustness in case of thickness variations along the studied object. The method has also been applied for vessel quantification and computer-aided diagnosis of vascular pathologies in angiographic data, providing promising results.