5 research outputs found
Bifurcated topological optimization for IVIM
In this work, we shed light on the issue of estimating Intravoxel Incoherent Motion (IVIM)
for diffusion and perfusion estimation by characterizing the objective function using
simplicial homology tools. We provide a robust solution via topological optimization of
this model so that the estimates are more reliable and accurate. Estimating the tissue
microstructure from diffusion MRI is in itself an ill-posed and a non-linear inverse problem.
Using variable projection functional (VarPro) to fit the standard bi-exponential IVIM model
we perform the optimization using simplicial homology based global optimization to
better understand the topology of objective function surface. We theoretically show
how the proposed methodology can recover the model parameters more accurately
and consistently by casting it in a reduced subspace given by VarPro. Additionally
we demonstrate that the IVIM model parameters cannot be accurately reconstructed
using conventional numerical optimization methods due to the presence of infinite
solutions in subspaces. The proposed method helps uncover multiple global minima by
analyzing the local geometry of the model enabling the generation of reliable estimates
of model parameters.The National Institute of Biomedical Imaging And Bioengineering (NIBIB) of the National Institutes of Health (NIH); University of Washington’s Royalty Research Fund; NIH grants; the German Research Foundation (DFG) and a grant from the Alfred P. Sloan Foundation and the Gordon & Betty Moore Foundation to the University of Washington eScience Institute Data Science Environment.http://www.frontiersin.org/Neuroscienceam2022Chemical Engineerin
Algorithmic Analysis Techniques for Molecular Imaging
This study addresses image processing techniques for two medical imaging
modalities: Positron Emission Tomography (PET) and Magnetic Resonance
Imaging (MRI), which can be used in studies of human body functions and
anatomy in a non-invasive manner.
In PET, the so-called Partial Volume Effect (PVE) is caused by low
spatial resolution of the modality. The efficiency of a set of PVE-correction
methods is evaluated in the present study. These methods use information
about tissue borders which have been acquired with the MRI technique. As
another technique, a novel method is proposed for MRI brain image segmen-
tation. A standard way of brain MRI is to use spatial prior information
in image segmentation. While this works for adults and healthy neonates,
the large variations in premature infants preclude its direct application.
The proposed technique can be applied to both healthy and non-healthy
premature infant brain MR images. Diffusion Weighted Imaging (DWI) is
a MRI-based technique that can be used to create images for measuring
physiological properties of cells on the structural level. We optimise the
scanning parameters of DWI so that the required acquisition time can be
reduced while still maintaining good image quality.
In the present work, PVE correction methods, and physiological DWI
models are evaluated in terms of repeatabilityof the results. This gives in-
formation on the reliability of the measures given by the methods. The
evaluations are done using physical phantom objects, correlation measure-
ments against expert segmentations, computer simulations with realistic
noise modelling, and with repeated measurements conducted on real pa-
tients. In PET, the applicability and selection of a suitable partial volume
correction method was found to depend on the target application. For MRI,
the data-driven segmentation offers an alternative when using spatial prior is
not feasible. For DWI, the distribution of b-values turns out to be a central
factor affecting the time-quality ratio of the DWI acquisition. An optimal
b-value distribution was determined. This helps to shorten the imaging time
without hampering the diagnostic accuracy.Siirretty Doriast
Molecular Imaging
The present book gives an exceptional overview of molecular imaging. Practical approach represents the red thread through the whole book, covering at the same time detailed background information that goes very deep into molecular as well as cellular level. Ideas how molecular imaging will develop in the near future present a special delicacy. This should be of special interest as the contributors are members of leading research groups from all over the world