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Accomplishments and challenges in stem cell imaging in vivo.
Stem cell therapies have demonstrated promising preclinical results, but very few applications have reached the clinic owing to safety and efficacy concerns. Translation would benefit greatly if stem cell survival, distribution and function could be assessed in vivo post-transplantation, particularly in patients. Advances in molecular imaging have led to extraordinary progress, with several strategies being deployed to understand the fate of stem cells in vivo using magnetic resonance, scintigraphy, PET, ultrasound and optical imaging. Here, we review the recent advances, challenges and future perspectives and opportunities in stem cell tracking and functional assessment, as well as the advantages and challenges of each imaging approach
Fast tomographic inspection of cylindrical objects
This paper presents a method for improved analysis of objects with an axial
symmetry using X-ray Computed Tomography (CT). Cylindrical coordinates about an
axis fixed to the object form the most natural base to check certain
characteristics of objects that contain such symmetry, as often occurs with
industrial parts. The sampling grid corresponds with the object, allowing for
down-sampling hence reducing the reconstruction time. This is necessary for
in-line applications and fast quality inspection. With algebraic reconstruction
it permits the use of a pre-computed initial volume perfectly suited to fit a
series of scans where same-type objects can have different positions and
orientations, as often encountered in an industrial setting. Weighted
back-projection can also be included when some regions are more likely subject
to change, to improve stability. Building on a Cartesian grid reconstruction
code, the feasibility of reusing the existing ray-tracers is checked against
other researches in the same field.Comment: 13 pages, 13 figures. submitted to Journal Of Nondestructive
Evaluation (https://www.springer.com/journal/10921
Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates
The study of cerebral anatomy in developing neonates is of great importance for
the understanding of brain development during the early period of life. This
dissertation therefore focuses on three challenges in the modelling of cerebral
anatomy in neonates during brain development. The methods that have been
developed all use Magnetic Resonance Images (MRI) as source data.
To facilitate study of vascular development in the neonatal period, a set of image
analysis algorithms are developed to automatically extract and model cerebral
vessel trees. The whole process consists of cerebral vessel tracking from
automatically placed seed points, vessel tree generation, and vasculature
registration and matching. These algorithms have been tested on clinical Time-of-
Flight (TOF) MR angiographic datasets.
To facilitate study of the neonatal cortex a complete cerebral cortex segmentation
and reconstruction pipeline has been developed. Segmentation of the neonatal
cortex is not effectively done by existing algorithms designed for the adult brain
because the contrast between grey and white matter is reversed. This causes pixels
containing tissue mixtures to be incorrectly labelled by conventional methods. The
neonatal cortical segmentation method that has been developed is based on a novel
expectation-maximization (EM) method with explicit correction for mislabelled
partial volume voxels. Based on the resulting cortical segmentation, an implicit
surface evolution technique is adopted for the reconstruction of the cortex in
neonates. The performance of the method is investigated by performing a detailed
landmark study.
To facilitate study of cortical development, a cortical surface registration algorithm
for aligning the cortical surface is developed. The method first inflates extracted
cortical surfaces and then performs a non-rigid surface registration using free-form
deformations (FFDs) to remove residual alignment. Validation experiments using
data labelled by an expert observer demonstrate that the method can capture local
changes and follow the growth of specific sulcus
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