Algorithmic depth compensation improves quantification and noise suppression in functional diffuse optical tomography
نویسندگان
چکیده
منابع مشابه
Algorithmic depth compensation improves quantification and noise suppression in functional diffuse optical tomography
Accurate depth localization and quantitative recovery of a regional activation are the major challenges in functional diffuse optical tomography (DOT). The photon density drops severely with increased depth, for which conventional DOT reconstruction yields poor depth localization and quantitative recovery. Recently we have developed a depth compensation algorithm (DCA) to improve the depth loca...
متن کاملAn Efficient Method for Model Reduction in Diffuse Optical Tomography
We present an efficient method for the reduction of model equations in the linearized diffuse optical tomography (DOT) problem. We first implement the maximum a posteriori (MAP) estimator and Tikhonov regularization, which are based on applying preconditioners to linear perturbation equations. For model reduction, the precondition is split into two parts: the principal components are consid...
متن کاملdiffuse optical tomography: image reconstruction and verification
introduction: in this study, we intend to use diffuse optical tomography (dot) as a noninvasive, safe and low cost technique that can be considered as a functional imaging method and mention the importance of image reconstruction in accuracy and procession of image. one of the most important and fastest methods in image reconstruction is the boundary element method (bem). this method is introdu...
متن کاملFunctional Near Infrared Spectroscopy and Diffuse Optical Tomography in Neuroscience
CT scanning uses X-rays crossing the sample to image sections of the specimen in study. Specimen can be a living being, a part of if (e.g. the abdomen, a knee, the head, ...) or whatever non-living object. X-rays travel ballistically inside most of the materials (living tissue included), so measuring absorption of X-rays we can guess the composition of the sample we are measuring. Changing the ...
متن کاملModel-resolution based regularization improves near infrared diffuse optical tomography.
Diffuse optical tomographic imaging is known to be an ill-posed problem, and a penalty/regularization term is used in image reconstruction (inverse problem) to overcome this limitation. Two schemes that are prevalent are spatially varying (exponential) and constant (standard) regularizations/penalties. A scheme that is also spatially varying but uses the model information is introduced based on...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biomedical Optics Express
سال: 2010
ISSN: 2156-7085
DOI: 10.1364/boe.1.000441