Voxel-Wise Clustering of Tractography Data for Building Atlases of Local Fiber Geometry

2019 ◽  
pp. 345-357
Author(s):  
Irene Brusini ◽  
Daniel Jörgens ◽  
Örjan Smedby ◽  
Rodrigo Moreno
Keyword(s):  
Tractography Data ◽  
Local Fiber

Impact of fiber structure on edge-wicking of highly-sized paperboard

TAPPI Journal ◽  
2018 ◽  
Vol 17 (08) ◽  
pp. 437-443
Author(s):  
Lebo Xu ◽  
Jeremy Meyers ◽  
Peter Hart
Keyword(s):  
Fiber Surface ◽  
Manufacturing Processes ◽  
Paper Machine ◽  
Liquid Penetration ◽  
Fiber Structure ◽  
Cut Edge ◽  
Local Fiber

Coffee edge-wicking testing was conducted on two groups of highly-sized paperboard manufactured at two mills with similar manufacturing processes, but with vastly different local fiber sources. Although the Hercules size test (HST) indicated similar internal size levels between the two types of board, the edge-wicking behavior was noticeably different. Analysis of fiber structure revealed that the board with more edge-wicking had fibers with thicker fiber walls, which kept the fiber lumen more open after pressing and drying on a paper machine. It was demonstrated that liquid penetration through voids between fibers in highly-sized paperboard was limited, because the fiber surface was well protected by the presence of sufficient sizing agent. Nevertheless, freshly exposed fiber walls and lumens at the cut edge of the sheet were not protected by sizing material, which facilitated edge-wicking. The correlation between fiber structure and edge-wicking behavior was highlighted in this work to inspire development of novel sizing strategies that protect the freshly cut edge of the sheet from edge-wicking.

scholarly journals Retrospective analysis of hemispheric structural network change as a function of location and size of glioma

2020 ◽  
Author(s):  
Shawn D’Souza ◽  
Lisa Hirt ◽  
David R Ormond ◽  
John A Thompson
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Temporal Lobe ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Structural Network ◽  
Tumour Location ◽  
The Impact ◽  
Tractography Data ◽  
Diffusion Tensor Imaging Tractography

Abstract Gliomas are neoplasms that arise from glial cell origin and represent the largest fraction of primary malignant brain tumours (77%). These highly infiltrative malignant cell clusters modify brain structure and function through expansion, invasion and intratumoral modification. Depending on the growth rate of the tumour, location and degree of expansion, functional reorganization may not lead to overt changes in behaviour despite significant cerebral adaptation. Studies in simulated lesion models and in patients with stroke reveal both local and distal functional disturbances, using measures of anatomical brain networks. Investigations over the last two decades have sought to use diffusion tensor imaging tractography data in the context of intracranial tumours to improve surgical planning, intraoperative functional localization, and post-operative interpretation of functional change. In this study, we used diffusion tensor imaging tractography to assess the impact of tumour location on the white matter structural network. To better understand how various lobe localized gliomas impact the topology underlying efficiency of information transfer between brain regions, we identified the major alterations in brain network connectivity patterns between the ipsilesional versus contralesional hemispheres in patients with gliomas localized to the frontal, parietal or temporal lobe. Results were indicative of altered network efficiency and the role of specific brain regions unique to different lobe localized gliomas. This work draws attention to connections and brain regions which have shared structural susceptibility in frontal, parietal and temporal lobe glioma cases. This study also provides a preliminary anatomical basis for understanding which affected white matter pathways may contribute to preoperative patient symptomology.

Evaluating New York raw fiber-to-retail

2020 ◽  
Vol 35 (8) ◽  
pp. 787-807
Author(s):  
Helen X Trejo ◽  
Tasha L Lewis
Keyword(s):  
New York ◽  
Value Chain ◽  
Future Goals ◽  
Leadership Initiatives ◽  
Key Dimensions ◽  
Farm Business ◽  
Slow Fashion ◽  
Fiber Processing ◽  
Local Fiber

Inspired by the slow fashion movement, this is an exploratory case study focused on New York’s raw fiber-to-retail value chain for local clothing and textiles. New York has over 470 diverse sheep, alpaca, goat farms, fiber processing mills for product development, and fiber festivals for retail. A survey with farmers presents their motives for establishing a fiber farm business, diverse fibers available, fiber products, income, and their multiple retail venues. Interviews were conducted with farmers, fiber mill owners, and artisan designers. Primary research objectives included: (1) determining how fiber farms, mills, artisans, fiber festivals, and fiber agro-tourism intersect to sustain the current fiber community; (2) evaluating the major challenges the fiber community faces; (3) determining if stakeholders of the fiber community have benefited from any policies; and (4) understanding future goals New York raw fiber-to-fashion stakeholders have to sustain the local fiber community. Interviews reveal several leadership initiatives developed by fiber farmers to address challenges of finding a market, limited income, and fiber mill closures. This study uses the five key dimensions of slow fashion as a framework to evaluate New York raw fiber-to-retail.

scholarly journals Structural brain network topology underpinning ADHD and response to methylphenidate treatment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kristi R. Griffiths ◽  
Taylor A. Braund ◽  
Michael R. Kohn ◽  
Simon Clarke ◽  
Leanne M. Williams ◽  
...  
Keyword(s):  
Brain Network ◽  
Global Network ◽  
Support Vector ◽  
Structural Topology ◽  
Local Efficiency ◽  
Structural Brain Network ◽  
Structural Architecture ◽  
The Right ◽  
Tractography Data ◽  
Treatment Prognosis

AbstractBehavioural disturbances in attention deficit hyperactivity disorder (ADHD) are thought to be due to dysfunction of spatially distributed, interconnected neural systems. While there is a fast-growing literature on functional dysconnectivity in ADHD, far less is known about the structural architecture underpinning these disturbances and how it may contribute to ADHD symptomology and treatment prognosis. We applied graph theoretical analyses on diffusion MRI tractography data to produce quantitative measures of global network organisation and local efficiency of network nodes. Support vector machines (SVMs) were used for comparison of multivariate graph measures of 37 children and adolescents with ADHD relative to 26 age and gender matched typically developing children (TDC). We also explored associations between graph measures and functionally-relevant outcomes such as symptom severity and prediction of methylphenidate (MPH) treatment response. We found that multivariate patterns of reduced local efficiency, predominantly in subcortical regions (SC), were able to distinguish between ADHD and TDC groups with 76% accuracy. For treatment prognosis, higher global efficiency, higher local efficiency of the right supramarginal gyrus and multivariate patterns of increased local efficiency across multiple networks at baseline also predicted greater symptom reduction after 6 weeks of MPH treatment. Our findings demonstrate that graph measures of structural topology provide valuable diagnostic and prognostic markers of ADHD, which may aid in mechanistic understanding of this complex disorder.

scholarly journals A UNIFIED COMMUNITY DETECTION, VISUALIZATION AND ANALYSIS METHOD

2014 ◽  
Vol 17 (01) ◽  
pp. 1450001 ◽  
Author(s):  
MICHEL CRAMPES ◽  
MICHEL PLANTIÉ
Keyword(s):  
Community Detection ◽  
Directed Graphs ◽  
Real Data ◽  
Semantic Interpretation ◽  
Detection Methods ◽  
Analysis Method ◽  
Overlapping Communities ◽  
Social Graphs ◽  
Tractography Data ◽  
Research Domain

With the widespread social networks on the Internet, community detection in social graphs has recently become an important research domain. Interest was initially limited to unipartite graph inputs and partitioned community outputs. More recently, bipartite graphs, directed graphs and overlapping communities have all been investigated. Few contributions however have encompassed all three types of graphs simultaneously. In this paper, we present a method that unifies community detection for these three types of graphs while at the same time it merges partitioned and overlapping communities. Moreover, the results are visualized in a way that allows for analysis and semantic interpretation. For validation purposes this method is experimented on some well-known simple benchmarks and then applied to real data: photos and tags in Facebook and Human Brain Tractography data. This last application leads to the possibility of applying community detection methods to other fields such as data analysis with original enhanced performances.

scholarly journals Fiber_distance based unsupervised clustering method of MR tractography data

IBRO Reports ◽  
2019 ◽  
Vol 6 ◽  
pp. S524
Author(s):  
Sang-Han Choi ◽  
Young-Bo Kim ◽  
Zang-Hee Cho
Keyword(s):  
Unsupervised Clustering ◽  
Clustering Method ◽  
Tractography Data

scholarly journals Oriented collagen fibers direct tumor cell intravasation

2016 ◽  
Vol 113 (40) ◽  
pp. 11208-11213 ◽  
Author(s):  
Weijing Han ◽  
Shaohua Chen ◽  
Wei Yuan ◽  
Qihui Fan ◽  
Jianxiang Tian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Extracellular Matrix ◽  
Tumor Cell ◽  
Tumor Cells ◽  
Fiber Orientation ◽  
Breast Cancer Cells ◽  
Protein Concentration ◽  
Collagen Fiber ◽  
Fiber Alignment ◽  
Local Fiber

In this work, we constructed a Collagen I–Matrigel composite extracellular matrix (ECM). The composite ECM was used to determine the influence of the local collagen fiber orientation on the collective intravasation ability of tumor cells. We found that the local fiber alignment enhanced cell–ECM interactions. Specifically, metastatic MDA-MB-231 breast cancer cells followed the local fiber alignment direction during the intravasation into rigid Matrigel (∼10 mg/mL protein concentration).

scholarly journals Alterations in Microstructure and Local Fiber Orientation of White Matter Are Associated with Outcome after Mild Traumatic Brain Injury

2020 ◽  
Vol 37 (24) ◽  
pp. 2616-2623
Author(s):  
Mehrbod Mohammadian ◽  
Timo Roine ◽  
Jussi Hirvonen ◽  
Timo Kurki ◽  
Jussi P. Posti ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
White Matter ◽  
Mild Traumatic Brain Injury ◽  
Fiber Orientation ◽  
Local Fiber

Region-of-Interest X-Ray Tomography for the Non-Destructive Characterization of Local Fiber Orientation in Large Fiber Composite Parts

2019 ◽  
Vol 809 ◽  
pp. 587-593
Author(s):  
Simon Zabler ◽  
Katja Schladitz ◽  
Kilian Dremel ◽  
Jonas Graetz ◽  
Dascha Dobrovolskij
Keyword(s):  
Computed Tomography ◽  
Spatial Resolution ◽  
Fiber Orientation ◽  
Fiber Composite ◽  
Three Dimensional ◽  
Region Of Interest ◽  
Micro Computed Tomography ◽  
X Ray ◽  
Anisotropic Thermal Conductivity ◽  
Local Fiber

To detect and characterize materials defects in fiber composites as well as for evaluatingthe three-dimensional local fiber orientation in the latter, X-ray micro-CT is the preferred methodof choice. When micro computed tomography is applied to inspect large components, the method isreferred to as region-of-interest computed tomography. Parts can be as large as 10 cm wide and 1 mlong, while the measurement volume of micro computed tomography is a cylinder of only 4 − 5 mmdiameter (typical wall thickness of fiber composite parts). In this report, the potentials and limits ofregion-of-interest computed tomography are discussed with regard to spatial resolution and precisionwhen evaluating defects and local fiber orientation in squeeze cast components. The micro computedtomography scanner metRIC at Fraunhofer‘s Development Center X-ray Technology EZRT deliversregion-of-interest computed tomography up to a spatial resolution of 2 μm/voxel, which is sufficientfor determining the orientation of natural or synthetic fibers, wood, carbon and glass. The mean localfiber orientation is estimated on an isotropic structuring element of approximately 0.1 mm length bymeans of volume image analysis (MAVI software package by Fraunhofer ITWM). Knowing the exactlocal fiber orientation is critical for estimating anisotropic thermal conductivity and materials strength.

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