A novel algorithm to detect the baseline value of a time signal in Dynamic Contrast Enhanced-Computed Tomography

Dynamic Contrast Enhanced-Computed Tomography (DCE-CT) is a functional imaging technique that has aroused a great interest in several clinical applications. The unenhanced portion of DCE-CT signal, the baseline, plays a fundamental role for signal analysis as well as to achieve accurate clinical parameter values, such as perfusion ones, used for diagnosis and prognosis purposes. In this study, a new adaptive iterative algorithm to compute voxel-based baseline values exploiting the maximum number of samples, adaptively for each voxel, is proposed and compared against the three main approaches used in the literature, over a dataset of 30 DCE-CT perfusion (briefly, CTp) liver examinations. Results were evaluated according to classical statistical indexes and tests. The experiments show that voxel-based results achieved by applying the four approaches significantly differ and the error indexes related to our method are the lowest ones. Our results would expectedly improve the accuracy of all methods, including CTp, relying on the whole signal for computation of clinical parameters.