Graph-Assisted Visualization of Microvascular Networks

Microvessels are frequent targets for research into tissue development and disease progression. These complex and subtle differences between networks are currently difficult to visualize, making sample comparisons subjective and difficult to quantify. These challenges are due to the structure of microvascular networks, which are sparse but space-filling. This results in a complex and interconnected mesh that is difficult to represent and impractical to interpret using conventional visualization techniques. We develop a bi-modal visualization framework, leveraging graph-based and geometry-based techniques to achieve interactive visualization of microvascular networks. This framework allows researchers to objectively interpret the complex and subtle variations that arise when comparing microvascular networks.

[1]  Ibrahim T. Ozbolat,et al.  Cellular Based Strategies for Microvascular Engineering , 2019, Stem Cell Reviews and Reports.

[2]  Yoonsuck Choe,et al.  Fast macro-scale transmission imaging of microvascular networks using KESM , 2011, Biomedical optics express.

[3]  Ben Shneiderman,et al.  Tree-maps: a space-filling approach to the visualization of hierarchical information structures , 1991, Proceeding Visualization '91.

[4]  Cyrille Rossant,et al.  VisPy: Harnessing The GPU For Fast, High-Level Visualization , 2015 .

[5]  Yifan Hu,et al.  Efficient, High-Quality Force-Directed Graph Drawing , 2006 .

[6]  Arne Møller,et al.  The capillary dysfunction hypothesis of Alzheimer's disease , 2013, Neurobiology of Aging.

[7]  Stephen G. Kobourov,et al.  Spring Embedders and Force Directed Graph Drawing Algorithms , 2012, ArXiv.

[8]  D. Vittet,et al.  In Vitro Models of Vasculogenesis and Angiogenesis , 2001, Laboratory Investigation.

[9]  Ali Khademhosseini,et al.  Microengineered hydrogels for tissue engineering. , 2007, Biomaterials.

[10]  John H Slater,et al.  Fundamentals of Laser‐Based Hydrogel Degradation and Applications in Cell and Tissue Engineering , 2017, Advanced healthcare materials.

[11]  Ulrike von Luxburg,et al.  A tutorial on spectral clustering , 2007, Stat. Comput..

[12]  Derek Merck,et al.  Virtually Visualizing Vessels : A Study of the Annotation of Placental Vasculature from MRI in Large-scale Virtual Reality for Surgical Planning , 2016 .

[13]  Stavros J. Baloyannis,et al.  The Hypothalamus in Alzheimer’s Disease , 2015, American journal of Alzheimer's disease and other dementias.

[14]  Ivan Herman,et al.  Graph Visualization and Navigation in Information Visualization: A Survey , 2000, IEEE Trans. Vis. Comput. Graph..

[15]  John Keyser,et al.  Visualization of Cellular and Microvascular Relationships , 2008, IEEE Transactions on Visualization and Computer Graphics.

[16]  Kai Lawonn,et al.  Occlusion-free Blood Flow Animation with Wall Thickness Visualization , 2016, IEEE Transactions on Visualization and Computer Graphics.

[17]  Helen C. Purchase,et al.  Which Aesthetic has the Greatest Effect on Human Understanding? , 1997, GD.

[18]  Tiago P. Peixoto,et al.  The graph-tool python library , 2014 .

[19]  David Mayerich,et al.  Accurate flow in augmented networks (AFAN): an approach to generating three-dimensional biomimetic microfluidic networks with controlled flow , 2018, Analytical methods : advancing methods and applications.

[20]  Eduard Gröller,et al.  The VesselGlyph: focus & context visualization in CT-angiography , 2004, IEEE Visualization 2004.

[21]  Céline Fouard,et al.  A Novel Three‐Dimensional Computer‐Assisted Method for a Quantitative Study of Microvascular Networks of the Human Cerebral Cortex , 2006, Microcirculation.

[22]  Stavros J. Baloyannis,et al.  The vascular factor in Alzheimer's disease: A study in Golgi technique and electron microscopy , 2012, Journal of the Neurological Sciences.

[23]  Jeremy G. Siek,et al.  The Boost Graph Library - User Guide and Reference Manual , 2001, C++ in-depth series.

[24]  Robert J Zawadzki,et al.  Volumetric microvascular imaging of human retina using optical coherence tomography with a novel motion contrast technique. , 2009, Optics express.

[25]  Jaerock Kwon,et al.  Image Processing Pipeline for Web-Based Real-Time 3D Visualization of Teravoxel Volumes , 2018, DMBD.

[26]  Bojan Mohar,et al.  Isoperimetric numbers of graphs , 1989, J. Comb. Theory, Ser. B.

[27]  E. Takahashi,et al.  White and gray matter fiber pathways in autism spectrum disorder revealed by ex vivo diffusion MR tractography , 2016, Brain and behavior.

[28]  Edward M. Reingold,et al.  Graph drawing by force‐directed placement , 1991, Softw. Pract. Exp..

[29]  J. J. Moré,et al.  Estimation of sparse jacobian matrices and graph coloring problems , 1983 .

[30]  Elazer R Edelman,et al.  Vascular Tissue Engineering: Progress, Challenges, and Clinical Promise. , 2018, Cell stem cell.

[31]  Philipp J. Keller,et al.  Whole-brain functional imaging at cellular resolution using light-sheet microscopy , 2013, Nature Methods.

[32]  P. R. Hof,et al.  Pathological alterations of the cerebral microvasculature in Alzheimer's disease and related dementing disorders , 1994, Acta Neuropathologica.

[33]  Dai Fukumura,et al.  Tumor microvasculature and microenvironment: targets for anti-angiogenesis and normalization. , 2007, Microvascular research.

[34]  H. Chui,et al.  Microangiopathy, the vascular basement membrane and Alzheimer's disease: a review , 1990, Brain Research Bulletin.

[35]  Hans Hagen,et al.  Visual Exploration in Surgery Monitoring for Coronary Vessels , 2015 .

[36]  Jean-Daniel Fekete,et al.  NodeTrix: a Hybrid Visualization of Social Networks , 2007, IEEE Transactions on Visualization and Computer Graphics.

[37]  H. Seung,et al.  Serial two-photon tomography: an automated method for ex-vivo mouse brain imaging , 2011, Nature Methods.

[38]  Timo Ropinski,et al.  Survey of glyph-based visualization techniques for spatial multivariate medical data , 2011, Comput. Graph..

[39]  David Mayerich,et al.  Robust Tracing and Visualization of Heterogeneous Microvascular Networks , 2019, IEEE Transactions on Visualization and Computer Graphics.