A framework for validation of vessel segmentation algorithms

Abstract

Validation methods used in literature to evaluate vessel segmentation algorithms suffer to a great extent from objectiveness, reliability and reproducibility. This is because almost each group has its own way to evaluate an algorithms. In this paper, an extendable standardized evaluation framework for quantitative validation of vessel segmentation algorithms is presented. As ground-truth, it uses a physical vascular model to simulate the growth of vessels within organ masks extracted from clinical CT datasets. A set of image- and graph- based evaluation metrics are calculated to analyze various aspects of the algorithms under study. Using the proposed framework helps to meet the aforementioned quality criteria.