Patient specific reconstruction of vascular network for hemodynamic modeling
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Patient specific reconstruction of vascular network for hemodynamic modeling
Yury Ivanov (INM RAS), Roman Pryamonosov (MSU), 2014, Moscow
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3D reconstruction of vascular structure for patient-specific simulation
• CT, MRT diagnostic data in DICOM files• Image preprocessing• Performing vessels segmentation • Extraction of vascular structure• Geometric analysis and building topology of a vascular segment• Simulation with network blood circulation model
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3D vessel segmentationAmira3D Visualization and Analysis Software for Life Sciences and bio-medical datahttp://www.vsg3d.com/amira
• Volume of interest extraction• Arithmetic operation on images• Noise reduction with digital image
filters• Segmentation
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Extraction of vascular structure
VMTK (The Vascular Modeling Toolkit) - open source library, http://www.vmtk.org
Computing centerlines – convenient way of representation of tube-like structure as sets of center points and corresponding radiuses. Centerlines defined as centers of maximal inscribed spheres, calculated with Voronoi diagram method.
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Patient specific reconstruction of vascular network for haemodynamic modeling.
3D vascular domain: polygonal surface mesh and computed centerlines
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Export data into GUI and building of topology
• Export centerlines in VTK format• Converting to the internal format
of vessel representation.• Visualize 3D objects
• Perform hierarchical connectivity analysis: determination of intersection with consecutive building of node and branch tables. Every branch entry has information about pair of nodes, average radius and actual length (along the vessel axis)
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Patient specific reconstruction of vascular network for hemodynamic modeling
The vascular network of arterial part of systemic circulation based on virtual 3D model.(Realistic, detailed model of Circulatory System - http://www.plasticboy.co.uk/)
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Patient specific reconstruction of vascular network for hemodynamic modeling:
Aorta and coronary arteries segmentation
• Stack of DICOM files of size 512x512x248 (CT data)
• Slices of middle mediastinum: heart and lungs
Input data:
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Patient specific reconstruction of vascular network for hemodynamic modeling:
Result of aorta and coronary arteries segmentation
• Aorta is segmented with isoperimetric graph partitioning algorithm* (Leo Grady).
• Ostia points are detected as 2 aorta points of maximal Frangi Vesselness filter values.
• Arteries is segmented using Frangi Filter as connectivity components of ostia points.
* Isoperimetric distance tree
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Patient specific reconstruction of vascular network for hemodynamic modeling:
Result of skeletonization
• Result of distance-ordered homotopic thinning.
• Skeleton allows to build 1d tree or graph.
• 1-dimentional centerline tree contains information about lengths and average radiuses.
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