A priori fluorophore distribution estimation in fluorescence imaging through application of a segmentation process and a data fitting technique.
During the last few years a quite large number of fluorescence imaging applications have been reported in the literature, as one of the most challenging problems in medical imaging is to "see" a tumor embedded in tissue, which is a turbid medium. This problem has not been fully encountered yet, due to the non-linear nature of the inverse problem. In this paper, a novel method for processing the forward solver outcomes is presented. Through this technique the comparison between the simulated and the acquired data can be performed only at the region-of-interest, minimizing time-consuming pixel-to-pixel comparison. With this modus operandi a-priori information about the initial fluorophore distribution becomes available, leading to a more feasible inverse problem solution.
Gorpas
Dimitris
D
National Technical University of Athens, School of Electrical and Computer Engineering, Laboratory of Biomedical Optics and Applied Biophysics, 9 Heroon Polytechniou Street, Zografou Campus, 157 80 Zogragou, Greece. dgorpas@mail.ntua.gr
Yova
Dido
D
Politopoulos
Kostas
K
D000465:Algorithms; D003952:Diagnostic Imaging / Q000379:methods*; D020342:Finite Element Analysis; D005453:Fluorescence; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data; D019047:Phantoms, Imaging / Q000706:statistics & numerical data