8,291 research outputs found
Motion compensated micro-CT reconstruction for in-situ analysis of dynamic processes
This work presents a framework to exploit the synergy between Digital Volume Correlation ( DVC) and iterative CT reconstruction to enhance the quality of high-resolution dynamic X-ray CT (4D-mu CT) and obtain quantitative results from the acquired dataset in the form of 3D strain maps which can be directly correlated to the material properties. Furthermore, we show that the developed framework is capable of strongly reducing motion artifacts even in a dataset containing a single 360 degrees rotation
Insight into the fundamental trade-offs of diffusion MRI from polarization-sensitive optical coherence tomography in ex vivo human brain
In the first study comparing high angular resolution diffusion MRI (dMRI) in the human brain to axonal orientation measurements from polarization-sensitive optical coherence tomography (PSOCT), we compare the accuracy of orientation estimates from various dMRI sampling schemes and reconstruction methods. We find that, if the reconstruction approach is chosen carefully, single-shell dMRI data can yield the same accuracy as multi-shell data, and only moderately lower accuracy than a full Cartesian-grid sampling scheme. Our results suggest that current dMRI reconstruction approaches do not benefit substantially from ultra-high b-values or from very large numbers of diffusion-encoding directions. We also show that accuracy remains stable across dMRI voxel sizes of 1 ​mm or smaller but degrades at 2 ​mm, particularly in areas of complex white-matter architecture. We also show that, as the spatial resolution is reduced, axonal configurations in a dMRI voxel can no longer be modeled as a small set of distinct axon populations, violating an assumption that is sometimes made by dMRI reconstruction techniques. Our findings have implications for in vivo studies and illustrate the value of PSOCT as a source of ground-truth measurements of white-matter organization that does not suffer from the distortions typical of histological techniques.Published versio
Four-dimensional Cone Beam CT Reconstruction and Enhancement using a Temporal Non-Local Means Method
Four-dimensional Cone Beam Computed Tomography (4D-CBCT) has been developed
to provide respiratory phase resolved volumetric imaging in image guided
radiation therapy (IGRT). Inadequate number of projections in each phase bin
results in low quality 4D-CBCT images with obvious streaking artifacts. In this
work, we propose two novel 4D-CBCT algorithms: an iterative reconstruction
algorithm and an enhancement algorithm, utilizing a temporal nonlocal means
(TNLM) method. We define a TNLM energy term for a given set of 4D-CBCT images.
Minimization of this term favors those 4D-CBCT images such that any anatomical
features at one spatial point at one phase can be found in a nearby spatial
point at neighboring phases. 4D-CBCT reconstruction is achieved by minimizing a
total energy containing a data fidelity term and the TNLM energy term. As for
the image enhancement, 4D-CBCT images generated by the FDK algorithm are
enhanced by minimizing the TNLM function while keeping the enhanced images
close to the FDK results. A forward-backward splitting algorithm and a
Gauss-Jacobi iteration method are employed to solve the problems. The
algorithms are implemented on GPU to achieve a high computational efficiency.
The reconstruction algorithm and the enhancement algorithm generate visually
similar 4D-CBCT images, both better than the FDK results. Quantitative
evaluations indicate that, compared with the FDK results, our reconstruction
method improves contrast-to-noise-ratio (CNR) by a factor of 2.56~3.13 and our
enhancement method increases the CNR by 2.75~3.33 times. The enhancement method
also removes over 80% of the streak artifacts from the FDK results. The total
computation time is ~460 sec for the reconstruction algorithm and ~610 sec for
the enhancement algorithm on an NVIDIA Tesla C1060 GPU card.Comment: 20 pages, 3 figures, 2 table
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Lensfree computational microscopy tools for cell and tissue imaging at the point-of-care and in low-resource settings.
The recent revolution in digital technologies and information processing methods present important opportunities to transform the way optical imaging is performed, particularly toward improving the throughput of microscopes while at the same time reducing their relative cost and complexity. Lensfree computational microscopy is rapidly emerging toward this end, and by discarding lenses and other bulky optical components of conventional imaging systems, and relying on digital computation instead, it can achieve both reflection and transmission mode microscopy over a large field-of-view within compact, cost-effective and mechanically robust architectures. Such high throughput and miniaturized imaging devices can provide a complementary toolset for telemedicine applications and point-of-care diagnostics by facilitating complex and critical tasks such as cytometry and microscopic analysis of e.g., blood smears, Pap tests and tissue samples. In this article, the basics of these lensfree microscopy modalities will be reviewed, and their clinically relevant applications will be discussed
Computer-assisted access to the kidney
OBJECTIVES: The aim of this paper is to introduce the principles of
computer-assisted access to the kidney. The system provides the surgeon with a
pre-operative 3D planning on computed tomography (CT) images. After a rigid
registration with space-localized ultrasound (US) data, preoperative planning
can be transferred to the intra-operative conditions and an intuitive
man-machine interface allows the user to perform a puncture. MATERIAL AND
METHODS: Both CT and US images of informed normal volunteer were obtained to
perform calculation on the accuracy of registration and punctures were carried
out on a kidney phantom to measure the precision of the whole of the system.
RESULTS: We carried out millimetric registrations on real data and guidance
experiments on a kidney phantom showed encouraging results of 4.7 mm between
planned and reached targets. We noticed that the most significant error was
related to the needle deflection during the puncture. CONCLUSION: Preliminary
results are encouraging. Further work will be undertaken to improve efficiency
and accuracy, and to take breathing into account
Standardized Platform for Coregistration of Noncurrent Diffuse Optical and Magnetic Resonance Breast Images Obtained in Different Geometries
We present a novel methodology for combining breast image data obtained at different times, in different geometries, and by different techniques. We combine data based on diffuse optical tomography (DOT) and magnetic resonance imaging (MRI). The software platform integrates advanced multimodal registration and segmentation algorithms, requires minimal user experience, and employs computationally efficient techniques. The resulting superposed 3-D tomographs facilitate tissue analyses based on structural and functional data derived from both modalities, and readily permit enhancement of DOT data reconstruction using MRI-derived a-priori structural information. We demonstrate the multimodal registration method using a simulated phantom, and we present initial patient studies that confirm that tumorous regions in a patient breast found by both imaging modalities exhibit significantly higher total hemoglobin concentration (THC) than surrounding normal tissues. The average THC in the tumorous regions is one to three standard deviations larger than the overall breast average THC for all patients
Colocalization of neurons in optical coherence microscopy and Nissl-stained histology in Brodmann’s area 32 and area 21
Published in final edited form as:
Brain Struct Funct. 2019 January ; 224(1): 351–362. doi:10.1007/s00429-018-1777-z.Optical coherence tomography is an optical technique that uses backscattered light to highlight intrinsic structure, and when applied to brain tissue, it can resolve cortical layers and fiber bundles. Optical coherence microscopy (OCM) is higher resolution (i.e., 1.25 µm) and is capable of detecting neurons. In a previous report, we compared the correspondence of OCM acquired imaging of neurons with traditional Nissl stained histology in entorhinal cortex layer II. In the current method-oriented study, we aimed to determine the colocalization success rate between OCM and Nissl in other brain cortical areas with different laminar arrangements and cell packing density. We focused on two additional cortical areas: medial prefrontal, pre-genual Brodmann area (BA) 32 and lateral temporal BA 21. We present the data as colocalization matrices and as quantitative percentages. The overall average colocalization in OCM compared to Nissl was 67% for BA 32 (47% for Nissl colocalization) and 60% for BA 21 (52% for Nissl colocalization), but with a large variability across cases and layers. One source of variability and confounds could be ascribed to an obscuring effect from large and dense intracortical fiber bundles. Other technical challenges, including obstacles inherent to human brain tissue, are discussed. Despite limitations, OCM is a promising semi-high throughput tool for demonstrating detail at the neuronal level, and, with further development, has distinct potential for the automatic acquisition of large databases as are required for the human brain.Accepted manuscrip
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