Automatic segmentation of 3D micro-CT coronary vascular images

Although there are many algorithms available in the literature aimed at segmentation and model reconstruction of 3D angiographic images, many are focused on characterizing only a part of the vascular network. This study is motivated by the recent emerging prospects of whole-organ simulations in coronary hemodynamics, autoregulation and tissue oxygen delivery for which anatomically accurate vascular meshes of extended scale are highly desirable. The key requirements of a reconstruction technique for this purpose are automation of processing and sub-voxel accuracy. We have designed a vascular reconstruction algorithm which satisfies these two criteria. It combines automatic seeding and tracking of vessels with radius detection based on active contours. The method was first examined through a series of tests on synthetic data, for accuracy in reproduced topology and morphology of the network and was shown to exhibit errors of less than 0.5 voxel for centerline and radius detections, and 3 degrees for initial seed directions. The algorithm was then applied on real-world data of full rat coronary structure acquired using a micro-CT scanner at 20 microm voxel size. For this, a further validation of radius quantification was carried out against a partially rescanned portion of the network at 8 microm voxel size, which estimated less than 10% radius error in vessels larger than 2 voxels in radius.

[1]  P J H de Koning,et al.  Automated segmentation and analysis of vascular structures in magnetic resonance angiographic images , 2003, Magnetic resonance in medicine.

[2]  Stephen R. Aylward,et al.  Analyzing attributes of vessel populations , 2005, Medical Image Anal..

[3]  Nicolas Flasque,et al.  Acquisition, segmentation and tracking of the cerebral vascular tree on 3D magnetic resonance angiography images , 2001, Medical Image Anal..

[4]  Jeffrey L Clendenon,et al.  Voxx: a PC-based, near real-time volume rendering system for biological microscopy. , 2002, American journal of physiology. Cell physiology.

[5]  Max A. Viergever,et al.  Fast delineation and visualization of vessels in 3-D angiographic images , 2000, IEEE Transactions on Medical Imaging.

[6]  Y Sun,et al.  Automated identification of vessel contours in coronary arteriograms by an adaptive tracking algorithm. , 1989, IEEE transactions on medical imaging.

[7]  Jian Chen,et al.  Quantifying 3-D vascular structures in MRA images using hybrid PDE and geometric deformable models , 2004, IEEE Transactions on Medical Imaging.

[8]  B L Langille,et al.  Branching characteristics of coronary arteries in rats. , 1984, Canadian journal of physiology and pharmacology.

[9]  Ying Sun,et al.  Recursive tracking of vascular networks in angiograms based on the detection-deletion scheme , 1993, IEEE Trans. Medical Imaging.

[10]  Pascal Desgranges,et al.  Assessment of critical limb ischemia in patients with diabetes: comparison of MR angiography and digital subtraction angiography. , 2005, AJR. American journal of roentgenology.

[11]  Ghassan S. Kassab,et al.  Large-Scale 3-D Geometric Reconstruction of the Porcine Coronary Arterial Vasculature Based on Detailed Anatomical Data , 2005, Annals of Biomedical Engineering.

[12]  Martin Neumann,et al.  Staged Growth of Optimized Arterial Model Trees , 2000, Annals of Biomedical Engineering.

[13]  Ghassan S Kassab,et al.  Longitudinal position matrix of the pig coronary vasculature and its hemodynamic implications. , 1997, American journal of physiology. Heart and circulatory physiology.

[14]  Geert J. Streekstra,et al.  Visualisation of intramural coronary vasculature by an imaging cryomicrotome suggests compartmentalisation of myocardial perfusion areas , 2005, Medical and Biological Engineering and Computing.

[15]  David H. Eberly,et al.  Zoom-Invariant Vision of Figural Shape: The Mathematics of Cores , 1996, Comput. Vis. Image Underst..

[16]  James B. Bassingthwaighte,et al.  The Fractal Nature of Myocardial Blood Flow Emerges from a Whole-Organ Model of Arterial Network , 2000, Journal of Vascular Research.

[17]  L. Sarry,et al.  In vitro evaluation of 2D-digital subtraction angiography versus 3D-time-of-flight in assessment of intracranial cerebral aneurysm filling after endovascular therapy. , 2006, AJNR. American journal of neuroradiology.

[18]  Guido Gerig,et al.  3D Multi-scale line filter for segmentation and visualization of curvilinear structures in medical images , 1997, CVRMed.

[19]  Maciej Orkisz,et al.  Computer-assisted analysis of three-dimensional MR angiograms. , 2002, Radiographics : a review publication of the Radiological Society of North America, Inc.

[20]  L. Feldkamp,et al.  Practical cone-beam algorithm , 1984 .

[21]  Andrew J. Pullan,et al.  An Anatomically Based Model of Transient Coronary Blood Flow in the Heart , 2002, SIAM J. Appl. Math..

[22]  Bruce H Smaill,et al.  Automated imaging of extended tissue volumes using confocal microscopy , 2005, Microscopy research and technique.

[23]  Laurent D. Cohen,et al.  Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Laurent D. Cohen,et al.  On active contour models and balloons , 1991, CVGIP Image Underst..

[25]  Timothy W. Secomb,et al.  Green's Function Methods for Analysis of Oxygen Delivery to Tissue by Microvascular Networks , 2004, Annals of Biomedical Engineering.

[26]  Rafael Beyar,et al.  Analytical and Quantitative Cardiology , 2012, Advances in Experimental Medicine and Biology.

[27]  P. J. Hunter,et al.  Generation of an Anatomically Based Geometric Coronary Model , 2004, Annals of Biomedical Engineering.

[28]  Sabee Molloi,et al.  Automatic 3D vascular tree construction in CT angiography. , 2003, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[29]  G S Kassab,et al.  Morphometry of pig coronary arterial trees. , 1993, The American journal of physiology.

[30]  Michael Scholz,et al.  New methods for the computer-assisted 3-D reconstruction of neurons from confocal image stacks , 2004, NeuroImage.

[31]  Prashanthi Vemuri,et al.  Automatic Detection of Three-Dimensional Vascular Tree Centerlines and Bifurcations in High-Resolution Magnetic Resonance Angiography , 2005, Investigative radiology.

[32]  Nicholas Ayache,et al.  Model-Based Detection of Tubular Structures in 3D Images , 2000, Comput. Vis. Image Underst..

[33]  Arthur W. Toga,et al.  Efficient Skeletonization of Volumetric Objects , 1999, IEEE Trans. Vis. Comput. Graph..

[34]  G S Kassab,et al.  Diameter-defined Strahler system and connectivity matrix of the pulmonary arterial tree. , 1994, Journal of applied physiology.

[35]  L. Latour,et al.  Assessment of CE-MRA for the rapid detection of supra-aortic vascular disease , 2005, Neurology.

[36]  Stephen R. Aylward,et al.  Volume rendering of segmented image objects , 2002, IEEE Transactions on Medical Imaging.

[37]  Daniel A. Beard,et al.  Computational Framework for Generating Transport Models from Databases of Microvascular Anatomy , 2001, Annals of Biomedical Engineering.

[38]  S M Jorgensen,et al.  3D architecture of myocardial microcirculation in intact rat heart: a study with micro-CT. , 1997, Advances in experimental medicine and biology.

[39]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[40]  James B. Bassingthwaighte,et al.  Modeling Advection and Diffusion of Oxygen in Complex Vascular Networks , 2001, Annals of Biomedical Engineering.

[41]  S. Pizer,et al.  Intensity ridge and widths for tubular object segmentation and description , 1996, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.

[42]  E A Hoffman,et al.  Measurement of three-dimensional lung tree structures by using computed tomography. , 1995, Journal of applied physiology.

[43]  Axel R. Pries,et al.  Remodeling of Blood Vessels: Responses of Diameter and Wall Thickness to Hemodynamic and Metabolic Stimuli , 2005, Hypertension.

[44]  Venkatraman Sadanand,et al.  The Reliability of Ultrasound Measurements of Carotid Stenosis Compared to MRA and DSA , 2005, Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques.

[45]  Ali Shahrokni,et al.  Three-dimensional analysis of complex branching vessels in confocal microscopy images. , 2005, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[46]  L. Østergaard,et al.  Method for modelling cerebral blood vessels and their bifurcations using circular, homogeneous, generalised cylinders , 2004, Medical and Biological Engineering and Computing.

[47]  Du-Ming Tsai,et al.  MEASUREMENT OF ROUNDNESS : A NONLINEAR APPROACH , 1999 .

[48]  Stephen R. Aylward,et al.  Symbolic description of intracerebral vessels segmented from magnetic resonance angiograms and evaluation by comparison with X-ray angiograms , 2001, Medical Image Anal..

[49]  S M Jorgensen,et al.  Three-dimensional imaging of vasculature and parenchyma in intact rodent organs with X-ray micro-CT. , 1998, The American journal of physiology.

[50]  G S Kassab,et al.  Morphometry of pig coronary venous system. , 1994, The American journal of physiology.

[51]  J B Bassingthwaighte,et al.  BIFURCATING DISTRIBUTIVE SYSTEM USING MONTE CARLO METHOD. , 1992, Mathematical and computer modelling.

[52]  Stephen R. Aylward,et al.  Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction , 2002, IEEE Transactions on Medical Imaging.

[53]  Geoffrey McLennan,et al.  CT-based geometry analysis and finite element models of the human and ovine bronchial tree. , 2004, Journal of applied physiology.

[54]  Mie Sato,et al.  Penalized-Distance Volumetric Skeleton Algorithm , 2001, IEEE Trans. Vis. Comput. Graph..

[55]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[56]  Emmanuelle P Canet Soulas,et al.  Quantification of multicontrast vascular MR images with NLSnake, an active contour model: In vitro validation and in vivo evaluation , 2004, Magnetic resonance in medicine.

[57]  E. vanBavel,et al.  Branching patterns in the porcine coronary arterial tree. Estimation of flow heterogeneity. , 1992, Circulation research.

[58]  Amir A. Amini,et al.  Quantitative coronary angiography with deformable spline models , 1997, IEEE Transactions on Medical Imaging.

[59]  Guido Gerig,et al.  Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images , 1998, Medical Image Anal..

[60]  Jenny Dankelman,et al.  Balance between myogenic, flow-dependent, and metabolic flow control in coronary arterial tree: a model study. , 2002, American journal of physiology. Heart and circulatory physiology.

[61]  Stephane Cotin,et al.  A Segmentation and Reconstruction Technique for 3D Vascular Structures , 2005, MICCAI.

[62]  David A. Steinman,et al.  Robust and objective decomposition and mapping of bifurcating vessels , 2004, IEEE Transactions on Medical Imaging.

[63]  Alejandro F. Frangi,et al.  Model-based quantitation of 3-D magnetic resonance angiographic images , 1999, IEEE Transactions on Medical Imaging.

[64]  Nicolas P Smith,et al.  Structural morphology of renal vasculature. , 2006, American journal of physiology. Heart and circulatory physiology.