A priori fluorophore distribution estimation in fluorescence imaging through application of a segmentation process and a data fitting technique

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A priori fluorophore distribution estimation in fluorescence imaging through application of a segmentation process and a data fitting technique (EN)

Gorpas, D (EN)
Politopoulos, K (EN)
Yova, D (EN)

journalArticle (EN)

2014-03-01T01:32:31Z
2010 (EN)


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. (C) 2009 Elsevier Ltd. All rights reserved. (EN)

Radiology, Nuclear Medicine & Medical Imaging (EN)

Fluorescence molecular (EN)
Medical problems (EN)
Data handling (EN)
Finite Element (EN)
fluorescence imaging (EN)
simulation (EN)
Fluorescence (EN)
molecular imaging (EN)
image analysis (EN)
Pixels (EN)
Digital image storage (EN)
Finite Element Analysis (EN)
priority journal (EN)
Data fitting (EN)
Diffusion approximations (EN)
Diffusion approximation (EN)
Finite elements (EN)
Medical imaging (EN)
Data fittings (EN)
Fluorescence molecular imaging (EN)
article (EN)
Image segmentation (EN)
Diagnostic Imaging (EN)
Inverse problems (EN)
Algorithms (EN)
Image Processing, Computer-Assisted (EN)
Fluorophores (EN)
Phantoms, Imaging (EN)

Computerized Medical Imaging and Graphics (EN)

English

PERGAMON-ELSEVIER SCIENCE LTD (EN)




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