Ground truth and CT image model simulation for pathophysiological human airway system

Recurrent problem in medical image segmentation and analysis, establishing a ground truth for assessment purposes is often difficult. Facing this problem, the scientific community orients its efforts towards the development of objective methods for evaluation, namely by building up or simulating the missing ground truth for analysis. This paper focuses on the case of human pulmonary airways and develops a method 1) to simulate the ground truth for different pathophysiological configurations of the bronchial tree as a mesh model, and 2) to generate synthetic 3D CT images of airways associated with the simulated ground truth. The airway model is here built up based on the information provided by a medial axis (describing bronchus shape, subdivision geometry and local radii), which is computed from real CT data to ensure realism and matching with a patient-specific morphology. The model parameters can be further on adjusted to simulate various pathophysiological conditions of the same patient (longitudinal studies). Based on the airway mesh model, a 3D image model is synthesized by simulating the CT acquisition process. The image realism is achieved by including textural features of the surrounding pulmonary tissue which are obtained by segmentation from the same original CT data providing the airway axis. By varying the scanning simulation parameters, several 3D image models can be generated for the same airway mesh ground truth. Simulation results for physiological and pathological configurations are presented and discussed, illustrating the interest of such a modeling process for designing computer-aided diagnosis systems or for assessing their sensitivity, mainly for follow-up studies in asthma and COPD.