New methods for the geometrical analysis of tubular organs

HighlightsA new orthogonal plane estimator for tubular organs is proposed.It can be used directly on the 3D segmented organ.Orthogonal planes allow us to refine existing skeletons by pruning and recentering.We also use orthogonal planes to compute our own curve‐skeleton.The proposed methods are robust to noise, irregularities, and handle bifurcations. Graphical abstract Figure. No caption available. ABSTRACT This paper presents new methods to study the shape of tubular organs. Determining precise cross‐sections is of major importance to perform geometrical measurements, such as diameter, wall‐thickness estimation or area measurement. Our first contribution is a robust method to estimate orthogonal planes based on the Voronoi Covariance Measure. Our method is not relying on a curve‐skeleton computation beforehand. This means our orthogonal plane estimator can be used either on the skeleton or on the volume. Another important step towards tubular organ characterization is achieved through curve‐skeletonization, as skeletons allow to compare two tubular organs, and to perform virtual endoscopy. Our second contribution is dedicated to correcting common defects of the skeleton by new pruning and recentering methods. Finally, we propose a new method for curve‐skeleton extraction. Various results are shown on different types of segmented tubular organs, such as neurons, airway‐tree and blood vessels.

[1]  Michel Couprie,et al.  Discrete bisector function and Euclidean skeleton in 2D and 3D , 2007, Image Vis. Comput..

[2]  K. Furie,et al.  Heart disease and stroke statistics--2008 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. , 2007, Circulation.

[3]  Jong Beom Ra,et al.  Vessel cross-section determination based on nonrigid registration and electric field model , 2006, SPIE Medical Imaging.

[4]  Leonidas J. Guibas,et al.  Voronoi-Based Curvature and Feature Estimation from Point Clouds , 2011, IEEE Transactions on Visualization and Computer Graphics.

[5]  Robert M. Haralick,et al.  A Statistical, Nonparametric Methodology for Document Degradation Model Validation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  K. Furie,et al.  Heart disease and stroke statistics--2007 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. , 2008, Circulation.

[7]  Deborah Silver,et al.  Curve-Skeleton Properties, Applications, and Algorithms , 2007, IEEE Trans. Vis. Comput. Graph..

[8]  Milan Sonka,et al.  Quantitative analysis of pulmonary airway tree structures , 2006, Comput. Biol. Medicine.

[9]  Aly A. Farag,et al.  Variational Curve Skeletons Using Gradient Vector Flow , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Gabriella Sanniti di Baja,et al.  Pruning the 3D Curve Skeleton , 2014, 2014 22nd International Conference on Pattern Recognition.

[11]  Alan D. Lopez,et al.  Evidence-Based Health Policy--Lessons from the Global Burden of Disease Study , 1996, Science.

[12]  Alfred M. Bruckstein,et al.  Pruning Medial Axes , 1998, Comput. Vis. Image Underst..

[13]  Jean-Philippe Domenger,et al.  Centerlines of Tubular Volumes Based on Orthogonal Plane Estimation , 2016, DGCI.

[14]  L. Xing,et al.  Tracking the motion trajectories of junction structures in 4D CT images of the lung , 2012, Physics in medicine and biology.

[15]  Andrea Tagliasacchi,et al.  3 D Skeletons : A State-ofthe-Art Report , 2016 .

[16]  Stephen T. C. Wong,et al.  Robust 3D reconstruction and identification of dendritic spines from optical microscopy imaging , 2009, Medical Image Anal..

[17]  Gabriella Sanniti di Baja,et al.  Euclidean skeleton via centre-of-maximal-disc extraction , 1993, Image Vis. Comput..

[18]  Attila Kuba,et al.  Directional 3D Thinning Using 8 Subiterations , 1999, DGCI.

[19]  Jacques-Olivier Lachaud,et al.  Precise Cross-Section Estimation on Tubular Organs , 2015, CAIP.

[20]  William R. Gray Roncal,et al.  Saturated Reconstruction of a Volume of Neocortex , 2015, Cell.

[21]  Jacques-Olivier Lachaud,et al.  Voronoi-Based Geometry Estimator for 3D Digital Surfaces , 2014, DGCI.

[22]  Marleen de Bruijne,et al.  Vessel-guided airway tree segmentation: A voxel classification approach , 2010, Medical Image Anal..

[23]  Anca Dima Computer aided image segmentation and graph construction of nerve cells from 3D confocal microscopy scans , 2003 .

[24]  Chokri Ben Amar,et al.  Combining Different Reconstruction Kernel Responses as Preprocessing Step for Airway Tree Extraction in CT Scan , 2017, VISIGRAPP.

[25]  Riccardo Scateni,et al.  Skeleton Lab: an Interactive Tool to Create, Edit, and Repair Curve-Skeletons , 2015, STAG.

[26]  Jacques-Olivier Lachaud,et al.  Tangent estimation along 3D digital curves , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[27]  Rangasami L. Kashyap,et al.  Building Skeleton Models via 3-D Medial Surface/Axis Thinning Algorithms , 1994, CVGIP Graph. Model. Image Process..

[28]  Andrea Tagliasacchi,et al.  3D Skeletons: A State‐of‐the‐Art Report , 2016, Comput. Graph. Forum.

[29]  S BradleyRobert,et al.  Post-processing techniques for making reliable measurements from curve-skeletons , 2016 .

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

[31]  Alexandru Telea,et al.  Comparison of curve and surface skeletonization methods for voxel shapes , 2014, Pattern Recognit. Lett..

[32]  Timm Weitkamp,et al.  Three-dimensional quantification of capillary networks in healthy and cancerous tissues of two mice. , 2012, Microvascular research.

[33]  Philip J. Withers,et al.  Post-processing techniques for making reliable measurements from curve-skeletons , 2016, Comput. Biol. Medicine.

[34]  Horst Bischof,et al.  Extracting Curve Skeletons from Gray Value Images for Virtual Endoscopy , 2008, MIAR.

[35]  Jacques-Olivier Lachaud,et al.  Robust Geometry Estimation Using the Generalized Voronoi Covariance Measure , 2014, SIAM J. Imaging Sci..

[36]  Balasubramanian Raman,et al.  Computing hierarchical curve-skeletons of 3D objects , 2005, The Visual Computer.

[37]  Milan Sonka,et al.  Intrathoracic airway trees: segmentation and airway morphology analysis from low-dose CT scans , 2005, IEEE Transactions on Medical Imaging.