Data Specific Spatially Varying Regularization for Multimodal Fluorescence Molecular Tomography
نویسندگان
چکیده
منابع مشابه
Spatially varying regularization based on spectrally resolved fluorescence emission in fluorescence molecular tomography.
Fluorescence molecular tomography suffers from being mathematically ill-conditioned resulting in non-unique solutions to the reconstruction problem. In an attempt to reduce the number of possible solutions in the underdetermined system of equations in the reconstruction, we present a method to retrieve a spatially varying regularization map outlining the feasible inclusion position. This approa...
متن کاملJoint L1 and total variation regularization for fluorescence molecular tomography.
Fluorescence molecular tomography (FMT) is an imaging modality that exploits the specificity of fluorescent biomarkers to enable 3D visualization of molecular targets and pathways in vivo in small animals. Owing to the high degree of absorption and scattering of light through tissue, the FMT inverse problem is inherently ill-conditioned making image reconstruction highly susceptible to the effe...
متن کاملComparison of Regularization Methods in Fluorescence Molecular Tomography
In vivo fluorescence molecular tomography (FMT) has been a popular functional imaging modality in research labs in the past two decades. One of the major difficulties of FMT lies in the ill-posed and ill-conditioned nature of the inverse problem in reconstructing the distribution of fluorophores inside objects. The popular regularization methods based on L, L and total variation (TV ) norms hav...
متن کاملSelection of Varying Spatially Adaptive Regularization Parameter for Image Deconvolution
The deconvolution in image processing is an inverse illposed problem which necessitates a trade-off between delity to data and smoothness of a solution adjusted by a regularization parameter. In this paper we propose two techniques for selection of a varying regularization parameter minimizing the mean squared error for every pixel of the image. The rst algorithm uses the estimate of the square...
متن کاملVisualizing Spatially Varying Distribution Data
Box plot is a compact representation that encodes the minimum, maximum, mean, median, and quartile information of a distribution. In practice, a single box plot is ttrawn for each variable of interest. With the advent of more accessible computing power, we are now facing the problem of visualizing data where there is a distribution at each 2D spatial location. Simply extending the box plot tech...
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: IEEE Transactions on Medical Imaging
سال: 2010
ISSN: 0278-0062,1558-254X
DOI: 10.1109/tmi.2009.2031112