On the Spatial Resolution of Diffuse Optical Tomography

2000 ◽  
Author(s):  
Xavier Intes ◽  
Vasilis Ntziachristos ◽  
Monica Holboke ◽  
Arjun Yodh ◽  
Britton Chance
Keyword(s):  
Spatial Resolution ◽  
Optical Tomography ◽  
Diffuse Optical Tomography

scholarly journals Optimal Analysis Method for Dynamic Contrast-Enhanced Diffuse Optical Tomography

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Michael Ghijsen ◽  
Yuting Lin ◽  
Mitchell Hsing ◽  
Orhan Nalcioglu ◽  
Gultekin Gulsen
Keyword(s):  
Spatial Resolution ◽  
Animal Studies ◽  
Imaging Modality ◽  
A Priori ◽  
Optical Tomography ◽  
Diffuse Optical Tomography ◽  
Dynamic Contrast Enhanced ◽  
Promising Tool ◽  
Reconstruction Methods ◽  
Contrast Enhanced

Diffuse Optical Tomography (DOT) is an optical imaging modality that has various clinical applications. However, the spatial resolution and quantitative accuracy of DOT is poor due to strong photon scatting in biological tissue. Structurala prioriinformation from another high spatial resolution imaging modality such as Magnetic Resonance Imaging (MRI) has been demonstrated to significantly improve DOT accuracy. In addition, a contrast agent can be used to obtain differential absorption images of the lesion by using dynamic contrast enhanced DOT (DCE-DOT). This produces a relative absorption map that consists of subtracting a reconstructed baseline image from reconstructed images in which optical contrast is included. In this study, we investigated and compared different reconstruction methods and analysis approaches for regular endogenous DOT and DCE-DOT with and without MR anatomicala prioriinformation for arbitrarily-shaped objects. Our phantom and animal studies have shown that superior image quality and higher accuracy can be achieved using DCE-DOT together with MR structurala prioriinformation. Hence, implementation of a combined MRI-DOT system to image ICG enhancement can potentially be a promising tool for breast cancer imaging.

scholarly journals Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography

2012 ◽  
Vol 20 (18) ◽  
pp. 20427 ◽  
Author(s):  
Takeaki Shimokawa ◽  
Takashi Kosaka ◽  
Okito Yamashita ◽  
Nobuo Hiroe ◽  
Takashi Amita ◽  
...  
Keyword(s):  
Bayesian Estimation ◽  
Spatial Resolution ◽  
Optical Tomography ◽  
Diffuse Optical Tomography ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Estimation

scholarly journals Spatial resolution in depth for time-resolved diffuse optical tomography using short source-detector separations

2014 ◽  
Vol 6 (1) ◽  
pp. 1 ◽  
Author(s):  
Agathe Puszka ◽  
Laura Di Sieno ◽  
Alberto Dalla Mora ◽  
Antonio Pifferi ◽  
Davide Contini ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Optical Tomography ◽  
Diffuse Optical Tomography ◽  
Time Resolved

scholarly journals Ultimate spatial resolution
with Diffuse Optical Tomography

2009 ◽  
Vol 17 (14) ◽  
pp. 12132 ◽  
Author(s):  
Leila Azizi ◽  
Katarzyna Zarychta ◽  
Dominique Ettori ◽  
Eric Tinet ◽  
Jean-Michel Tualle
Keyword(s):  
Spatial Resolution ◽  
Optical Tomography ◽  
Diffuse Optical Tomography

scholarly journals Numerical modelling and image reconstruction in diffuse optical tomography

2009 ◽  
Vol 367 (1900) ◽  
pp. 3073-3093 ◽  
Author(s):  
Hamid Dehghani ◽  
Subhadra Srinivasan ◽  
Brian W. Pogue ◽  
Adam Gibson
Keyword(s):  
Image Reconstruction ◽  
Numerical Modelling ◽  
Spatial Resolution ◽  
Light Propagation ◽  
Light Transmission ◽  
Imaging Modality ◽  
Optical Tomography ◽  
Diffuse Optical Tomography ◽  
Optical Parameters ◽  
Model Based

The development of diffuse optical tomography as a functional imaging modality has relied largely on the use of model-based image reconstruction. The recovery of optical parameters from boundary measurements of light propagation within tissue is inherently a difficult one, because the problem is nonlinear, ill-posed and ill-conditioned. Additionally, although the measured near-infrared signals of light transmission through tissue provide high imaging contrast, the reconstructed images suffer from poor spatial resolution due to the diffuse propagation of light in biological tissue. The application of model-based image reconstruction is reviewed in this paper, together with a numerical modelling approach to light propagation in tissue as well as generalized image reconstruction using boundary data. A comprehensive review and details of the basis for using spatial and structural prior information are also discussed, whereby the use of spectral and dual-modality systems can improve contrast and spatial resolution.

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