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Titolo:
Use of penalty terms in gradient-based iterative reconstruction schemes for optical tomography
Autore:
Hielscher, AH; Bartel, S;
Indirizzi:
Polytech Univ, Dept Elect & Comp Engn, MetroTech Ctr 5, Brooklyn, NY 11201USA Polytech Univ Brooklyn NY USA 11201 etroTech Ctr 5, Brooklyn, NY 11201USA Suny Downstate Med Ctr, Dept Pathol, Brooklyn, NY 11203 USA Suny DownstateMed Ctr Brooklyn NY USA 11203 thol, Brooklyn, NY 11203 USA
Titolo Testata:
JOURNAL OF BIOMEDICAL OPTICS
fascicolo: 2, volume: 6, anno: 2001,
pagine: 183 - 192
SICI:
1083-3668(200104)6:2<183:UOPTIG>2.0.ZU;2-T
Fonte:
ISI
Lingua:
ENG
Soggetto:
FREQUENCY-DOMAIN DATA; IMAGE-RECONSTRUCTION; OPTIMIZATION SCHEME; TURBID MEDIA; ABSORPTION; MINIMIZATION; SIMULATIONS; FORMULATION; EQUATION; DENSITY;
Keywords:
optical tomography; image reconstruction; regularization; inverse problem;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Engineering, Computing & Technology
Citazioni:
44
Recensione:
Indirizzi per estratti:
Indirizzo: Hielscher, AH Suny Downstate Med Ctr, Dept Pathol, 450 Clarkson Ave,Box 25, Brooklyn, NY11203 USA Suny Downstate Med Ctr 450 Clarkson Ave,Box 25 Brooklyn NY USA 11203
Citazione:
A.H. Hielscher e S. Bartel, "Use of penalty terms in gradient-based iterative reconstruction schemes for optical tomography", J BIOMED OP, 6(2), 2001, pp. 183-192

Abstract

It is well known that the reconstruction problem in optical tomography is ill-posed. In other words, many different spatial distributions of optical properties inside the medium can lead to the same detector readings on the surface of the medium under consideration. Therefore, the choice of an appropriate method to overcome this problem is of crucial importance for any successful optical tomographic image reconstruction algorithm. In this work we approach the problem within a gradient-based iterative image reconstruction scheme. The image reconstruction is considered to be a minimization of an appropriately defined objective function. The objective function can be separated into a least-square-error term, which compares predicted and actual detector readings, and additional penalty terms that may contain a prioriinformation about the system. For the efficient minimization of this objective function the gradient with respect to the spatial distribution of optical properties is calculated. Besides presenting the underlying concepts inour approach to overcome ill-posedness in optical tomography, we will shownumerical results that demonstrate how prior knowledge, represented as penalty terms, can improve the reconstruction results. (C) 2001 society of Photo-Optical Instrumentation Engineers.

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Documento generato il 18/01/20 alle ore 21:27:58