scholarly journals Segmentation-Less, Automated, Vascular Vectorization

2021 ◽  
Vol 17 (10) ◽  
pp. e1009451
Author(s):  
Samuel A. Mihelic ◽  
William A. Sikora ◽  
Ahmed M. Hassan ◽  
Michael R. Williamson ◽  
Theresa A. Jones ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Statistical Power ◽  
Large Scale ◽  
Volume Fraction ◽  
Three Dimensional ◽  
Vascular Anatomy ◽  
Input Image ◽  
Segmented Images ◽  
Vessel Networks

Recent advances in two-photon fluorescence microscopy (2PM) have allowed large scale imaging and analysis of blood vessel networks in living mice. However, extracting network graphs and vector representations for the dense capillary bed remains a bottleneck in many applications. Vascular vectorization is algorithmically difficult because blood vessels have many shapes and sizes, the samples are often unevenly illuminated, and large image volumes are required to achieve good statistical power. State-of-the-art, three-dimensional, vascular vectorization approaches often require a segmented (binary) image, relying on manual or supervised-machine annotation. Therefore, voxel-by-voxel image segmentation is biased by the human annotator or trainer. Furthermore, segmented images oftentimes require remedial morphological filtering before skeletonization or vectorization. To address these limitations, we present a vectorization method to extract vascular objects directly from unsegmented images without the need for machine learning or training. The Segmentation-Less, Automated, Vascular Vectorization (SLAVV) source code in MATLAB is openly available on GitHub. This novel method uses simple models of vascular anatomy, efficient linear filtering, and vector extraction algorithms to remove the image segmentation requirement, replacing it with manual or automated vector classification. Semi-automated SLAVV is demonstrated on three in vivo 2PM image volumes of microvascular networks (capillaries, arterioles and venules) in the mouse cortex. Vectorization performance is proven robust to the choice of plasma- or endothelial-labeled contrast, and processing costs are shown to scale with input image volume. Fully-automated SLAVV performance is evaluated on simulated 2PM images of varying quality all based on the large (1.4×0.9×0.6 mm3 and 1.6×108 voxel) input image. Vascular statistics of interest (e.g. volume fraction, surface area density) calculated from automatically vectorized images show greater robustness to image quality than those calculated from intensity-thresholded images.

scholarly journals Segmentation-less, automated vascular vectorization robustly extracts neurovascular network statistics from in vivo two-photon images

2020 ◽  
Author(s):  
Samuel A. Mihelic ◽  
William A. Sikora ◽  
Ahmed M. Hassan ◽  
Michael R. Williamson ◽  
Theresa A. Jones ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Statistical Power ◽  
Large Scale ◽  
Performance Metrics ◽  
Three Dimensional ◽  
Vascular Anatomy ◽  
Input Image ◽  
Network Graph ◽  
Two Photon

AbstractRecent advances in two-photon microscopy (2PM) have allowed large scale imaging and analysis of cortical blood vessel networks in living mice. However, extracting a network graph and vector representations for vessels remain bottlenecks in many applications. Vascular vectorization is algorithmically difficult because blood vessels have many shapes and sizes, the samples are often unevenly illuminated, and large image volumes are required to achieve good statistical power. State-of-the-art, three-dimensional, vascular vectorization approaches require a segmented/binary image, relying on manual or supervised-machine annotation. Therefore, voxel-by-voxel image segmentation is biased by the human annotator/trainer. Furthermore, segmented images oftentimes require remedial morphological filtering before skeletonization/vectorization. To address these limitations, we propose a vectorization method to extract vascular objects directly from unsegmented images. The Segmentation-Less, Automated, Vascular Vectorization (SLAVV) source code in MATLAB is openly available on GitHub. This novel method uses simple models of vascular anatomy, efficient linear filtering, and low-complexity vector extraction algorithms to remove the image segmentation requirement, replacing it with manual or automated vector classification. SLAVV is demonstrated on three in vivo 2PM image volumes of microvascular networks (capillaries, arterioles and venules) in the mouse cortex. Vectorization performance is proven robust to the choice of plasma- or endothelial-labeled contrast, and processing costs are shown to scale with input image volume. Fully-automated SLAVV performance is evaluated on various, simulated 2PM images based on the large, [1.4, 0.9, 0.6] mm input image, and performance metrics show greater robustness to image quality than an intensity-based thresholding approach.

Large-scale three-dimensional anisotropic topology optimization of variable-axial lightweight composite structures

2021 ◽  
pp. 1-15
Author(s):  
Yuqing Zhou ◽  
Tsuyoshi Nomura ◽  
Enpei Zhao ◽  
Kazuhiro Saitou
Keyword(s):  
Topology Optimization ◽  
Composite Structures ◽  
Large Scale ◽  
Volume Fraction ◽  
Three Dimensional ◽  
Optimization Method ◽  
Optimized Design ◽  
Adaptive Meshing ◽  
Design Synthesis ◽  
Fiber Placement

Abstract Variable-axial fiber-reinforced composites allow for local customization of fiber orientation and thicknesses. Despite their significant potential for performance improvement over the conventional multiaxial composites and metals, they pose challenges in design optimization due to the vastly increased design freedom in material orientations. This paper presents an anisotropic topology optimization method for designing large-scale, 3D variable-axial lightweight composite structures subject to multiple load cases. The computational challenges associated with large-scale 3D anisotropic topology optimization with extremely low volume fraction are addressed by a tensor-based representation of 3D orientation that would avoid the 2π periodicity of angular representations such as Euler angles, and an adaptive meshing scheme, which, in conjunction with PDE regularization of the density variables, refines the mesh where structural members appear and coarsens where there is void. The proposed method is applied to designing a heavy-duty drone frame subject to complex multi-loading conditions. Finally, the manufacturability gaps between the optimized design and the fabrication-ready design for Tailored Fiber Placement (TFP) is discussed, which motivates future work toward a fully-automated design synthesis.

Three-Dimensional Characterization of the Microstructure of Bioglass/Polyethylene Composite by X-Ray Microtomography

2007 ◽  
Vol 330-332 ◽  
pp. 503-506
Author(s):  
Xiao Wei Fu ◽  
Jie Huang ◽  
E.S. Thian ◽  
Serena Best ◽  
William Bonfield
Keyword(s):  
Spatial Distribution ◽  
Volume Fraction ◽  
Three Dimensional ◽  
X Ray ◽  
Polyethylene Composite ◽  
Bioactive Properties ◽  
Recent Developments ◽  
3D Information

A Bioglass® reinforced polyethylene (Bioglass®/polyethylene) composite has been prepared, which combines the high bioactivity of Bioglass® and the toughness of polyethylene. The spatial distribution of Bioglass® particles within the composite is important for the performance of composites in-vivo. Recent developments in X-ray microtomography (XμT) have made it possible to visualize internal and microstructural details with different X-ray absorbencies, nondestructively, and to acquire 3D information at high spatial resolution. In this study, the volume fraction and 3D spatial distribution of Bioglass® particles has been acquired quantitatively by XμT. The information obtained provides a foundation for understanding the mechanical and bioactive properties of the Bioglass®/polyethylene composites.

Large-Scale Three-Dimensional Anisotropic Topology Optimization of Variable-Axial Composite Structures

2020 ◽  
Author(s):  
Yuqing Zhou ◽  
Tsuyoshi Nomura ◽  
Enpei Zhao ◽  
Wei Zhang ◽  
Kazuhiro Saitou
Keyword(s):  
Topology Optimization ◽  
Composite Structures ◽  
Large Scale ◽  
Volume Fraction ◽  
Three Dimensional ◽  
Optimized Design ◽  
Adaptive Meshing ◽  
Design Synthesis ◽  
Fiber Placement ◽  
Future Work

Abstract Variable-axial fiber-reinforced composites allow for local customization of fiber orientation and thicknesses. Despite their significant potential for performance improvement over the conventional multiaxial composites and metals, they pose challenges in design optimization due to the vastly increased design freedom in material orientations. This paper presents an anisotropic topology optimization (TO) method for designing large-scale, 3D variable-axial composite structures. The computational challenge for large-scale 3D TO with extremely low volume fraction is addressed by a tensor-based representation of 3D orientation that would avoid the 2π periodicity of angular representation such as Eular angles, and an adaptive meshing scheme, which, in conjunction with PDE regularization of the density variables, refines the mesh where structural members appear and coarsens where there is void. The proposed method is applied to designing a heavy-duty drone frame subject to complex multi-loading conditions. Finally, the manufacturability gaps between the optimized design and the fabrication-ready design for Tailored Fiber Placement (TFP) is discussed, which motivates future work toward fully-automated design synthesis.

scholarly journals Zebrafish Vascular Quantification (ZVQ): a tool for quantification of three-dimensional zebrafish cerebrovascular architecture by automated image analysis

Development ◽  
2022 ◽  
Author(s):  
E. C. Kugler ◽  
J. Frost ◽  
V. Silva ◽  
K. Plant ◽  
K. Chhabria ◽  
...  
Keyword(s):  
Image Analysis ◽  
Rapid Assessment ◽  
Three Dimensional ◽  
Vascular Anatomy ◽  
Light Sheet ◽  
Automated Image Analysis ◽  
Cerebral Vasculature ◽  
Experimental Conditions ◽  
Branching Points

Zebrafish transgenic lines and light sheet fluorescence microscopy allow in-depth insights into three-dimensional vascular development in vivo. However, quantification of the zebrafish cerebral vasculature in 3D remains highly challenging. Here, we describe and test an image analysis workflow for 3D quantification of the total or regional zebrafish brain vasculature, called zebrafish vasculature quantification “ZVQ”. It provides the first landmark- or object-based vascular inter-sample registration of the zebrafish cerebral vasculature, producing Population Average Maps allowing rapid assessment of intra- and inter-group vascular anatomy. ZVQ also extracts a range of quantitative vascular parameters from a user-specified Region of Interest including volume, surface area, density, branching points, length, radius, and complexity. Application of ZVQ to thirteen experimental conditions, including embryonic development, pharmacological manipulations and morpholino induced gene knockdown, shows ZVQ is robust, allows extraction of biologically relevant information and quantification of vascular alteration, and can provide novel insights into vascular biology. To allow dissemination, the code for quantification, a graphical user interface, and workflow documentation are provided. Together, ZVQ provides the first open-source quantitative approach to assess the 3D cerebrovascular architecture in zebrafish.

Atherosclerosis imaging

ESC CardioMed ◽  
2018 ◽  
pp. 524-528
Author(s):  
Chun Yuan ◽  
Zach Miller ◽  
Jianming Cai
Keyword(s):  
Atherosclerotic Plaque ◽  
Large Scale ◽  
Three Dimensional ◽  
Plaque Imaging ◽  
Fibrous Cap ◽  
Intraplaque Haemorrhage ◽  
Clinical Events ◽  
Flexible Imaging ◽  
Atherosclerosis Imaging

Atherosclerosis imaging goes beyond the simple identification of luminal stenosis. Besides stenosis measurement, there are two main motivations for atherosclerosis imaging: one is to identify the so-called vulnerable plaque, defined as atherosclerotic plaque that poses increased risk of rupture and clinical events, such as heart attack or stroke; the other is to identify ‘positively remodelled’ plaques—plaques that grow outward from the lumen but cause minimal or no stenosis. Cardiovascular magnetic resonance (CMR) has histologically validated capabilities to characterize carotid plaque features in vivo, including a lipid-rich necrotic core, fibrous cap, intraplaque haemorrhage (IPH), calcification, and inflammation. A multicontrast two-dimensional imaging approach has been used in many prospective studies relating baseline CMR characteristics of carotid atherosclerosis with plaque progression and clinical events. These studies have demonstrated the importance of detecting IPH, lipid-rich necrotic cores, and fibrous caps. Building on these findings, a number of three-dimensional CMR techniques have been recently developed that allow higher spatial resolution plaque imaging and easier application clinically with short scan times. Three-dimensional plaque imaging offers flexible imaging plane and view angle analysis, large coverage, multivascular beds capability, and is a fast and cost-effective screening for clinical use. Atherosclerosis imaging has also been applied to detect plaques in other vascular beds such as the coronary artery, intracranial artery, and peripheral artery, although each bed comes with unique imaging needs. Large-scale studies are needed to determine the impact of atherosclerotic plaque CMR on patient outcomes.

Variation Characteristics of Reactive Plumes in the Process of Extinguishing Diesel Flame by Water Mist

2012 ◽  
Vol 260-261 ◽  
pp. 10-16
Author(s):  
Liang Wang ◽  
Shi Chuan Su
Keyword(s):  
Large Scale ◽  
Volume Fraction ◽  
Early Stage ◽  
Three Dimensional ◽  
Water Mist ◽  
Jet Flame ◽  
Eddy Structure ◽  
Cumulative Volume ◽  
Variation Characteristics ◽  
Important Significance

By using the three-dimensional governing equations of plumes, the cumulative volume fraction and the model of water suppress fire, the variation characteristics of the reactive plumes in the process of water mist suppress the diesel jet flame are studied. For the different effects of water mist and no water mist, the eddy structure of plume, averaged velocity and averaged temperature in the above of fire source are analyzed, respectively. It seems that there are expansibility and geometric symmetry for the eddy structure in the early stage of the water mist control. However, as a whole, the water mist has cooling effect for the plume area, and it can also reduce the spread velocity of plume. The large-scale structure can be formed quickly, and the temperature is affected by the droplet size and droplet density. However, for the case of no water mist, the bursting of smaller scale vortices can be enhanced, and its structural characteristic has an affect on the distribution of averaged temperature. Computational results have important significance for the water mist to be used in the ship engineer room.

Progress Towards Prospective Computational Imaging Studies of Hemodynamics and Vascular Disease in Humans

1999 ◽  
Author(s):  
David A. Steinman ◽  
Hanif M. Ladak ◽  
Jonathan B. Thomas ◽  
Jaques S. Milner ◽  
Donald H. Lee ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Vascular Anatomy ◽  
Computational Imaging ◽  
Resonance Imaging ◽  
Imaging Studies ◽  
Complex Flow ◽  
Model Studies ◽  
Computational Fluid Dynamics Cfd ◽  
Magnetic Resonance Imaging Mri

Abstract Magnetic resonance imaging (MRI) allows us to resolve vascular anatomy with submillimeter resolution non-invasively, making it possible to monitor the development of atherosclerosis in vivo (Skinner et al, 1995). Although imaging technology is not yet mature enough to simultaneously resolve the complex flow patterns, computational fluid dynamics (CFD) can reliably and efficiently model pulsatile flow in realistic, three-dimensional arterial geometries. By using imaged lumen geometry and flow rate as input parameters to such model studies, we can reconstruct the local in vivo hemodynamic environment.

scholarly journals Three-dimensional human axon tracts derived from cerebral organoids

2018 ◽  
Author(s):  
D. Kacy Cullen ◽  
Laura A. Struzyna ◽  
Dennis Jgamadze ◽  
Wisberty J. Gordián-Vélez ◽  
James Lim ◽  
...  
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Neural Tissue ◽  
Cortical Layer ◽  
List Type ◽  
Brain Circuits ◽  
Novel Strategy ◽  
Cellular Phenotypes ◽  
The Brain

SummaryReestablishing cerebral connectivity is a critical part of restoring neuronal network integrity and brain function after trauma, stroke, and neurodegenerative diseases. Creating transplantable axon tracts in the laboratory is a novel strategy for overcoming the common barriers limiting axon regeneration in vivo, including growth-inhibiting factors and the limited outgrowth capacity of mature neurons in the brain. We describe the generation and phenotype of three-dimensional human axon tracts derived from cerebral organoid tissue. These centimeter-long constructs are encased in an agarose shell that permits physical manipulation and are composed of discrete cellular regions spanned by axon tracts and dendrites, mirroring the separation of grey and white matter in the brain. Features of cerebral cortex also are emulated, as evidenced by the presence of neurons with different cortical layer phenotypes. This engineered neural tissue has the translational potential to reconstruct brain circuits by physically replacing discrete cortical neuron populations as well as long-range axon tracts in the brain.eTOC BlurbRestoring axonal connectivity after brain damage is crucial for improving neurological and cognitive function. Cullen, et al. have generated anatomically inspired, three-dimensional human axon tracts projecting from cerebral organoids in a transplantable format that may facilitate the reconstruction of large-scale brain circuits.HighlightsA neural tissue engineering approach is applied to human cerebral organoids.Three-dimensional axon tracts are generated in a transplantable format.The growth characteristics of the engineered axons are examined.The cellular phenotypes of the organoid tissue and axons are characterized.

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