Image-based assessment of uncertainty in quantification of carotid lumen

Measurements of the vessel lumen diameter are often used to determine the degree of atherosclerotic disease in carotid arteries. However, quantification results vary with imaging technique and acquisition settings. In this work, we aim at providing a tool, that quantifies the lumen diameter on different image datasets and gives an estimate of quantification uncertainties, so that they can be taken into consideration when evaluating and comparing measurements. For the segmentation of the vessel lumen we present an algorithm using ray-casting techniques and partial volume correction. We furthermore propose a scheme for analysis and exploration of the lumen diameter. Finally, we present clinically relevant application scenario, in which we explore agreement between lumen diameter estimations in corresponding CTA, CEMRA, TOF and subtraction images of carotid vessels with severe carotid atherosclerotic plaques.