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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 segmentation Amira 3D Visualization and Analysis Software for Life Sciences and bio-medical data 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, 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 -

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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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