Automated extraction of the aorta and the pulmonary artery in the mediastinum from 3D chest X-ray CT images using the medial line model

Abstract

We have developed a method of analyzing fluorescence signals from optically thick tissue, which can be used to extract important clinical information about tissue type and chemical composition. Our model describes the composite tissue spectrum in terms of contributions from fluorophores and absorbers which modulate the intrinsic fluorescence spectrum. Scattering is included empirically in the model by describing absorbing species with ‘attenuation spectra’, which include contributions from both absorption and scattering. We present an analysis of laser induced fluorescence data obtained from normal and atherosclerotic human artery wall in vitro. We show that the model can be used to separate effects due to fluorescence and absorption, and to deconvolute contributions from individual chromophores, extracting information about their relative concentrations. This information can be utilized to diagnose tissue type more accurately than empirical algorithms, and may potentially prove to be useful in determining the chemical composition of atherosclerotic lesions in vivo.