Skip to main content
SpringerLink
Log in

Knowledge management in image-based analysis of blood vessel structures

  • Regular Paper
  • Published:
Knowledge and Information Systems Aims and scope Submit manuscript

Abstract

We have detected the lack of a widely accepted knowledge representation model in the area of Blood Vessel analysis. We find that such a tool is needed for the future development of the field and our own research efforts. It will allow easy reuse of software pieces through appropriate abstractions, facilitating the development of innovative methods, procedures and applications. We include a thorough review of vascular morphology image analysis. After the identification of the key representation elements and operations, we propose a Vessel Knowledge Representation (VKR) model that would fill this gap. We give insights into its implementation based on standard Object-Oriented Programming tools and paradigms. The VKR would easily integrate with existing medical imaging and visualization software platforms, such as the Insight ToolKit (ITK) and Visualization Toolkit (VTK).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Adalsteinsson D, Sethian JA (1995) A fast level set method for propagating interfaces. J Comput Phys 118(2): 269–277

    Article  MATH  MathSciNet  Google Scholar 

  2. Agam G, Armato SG III, Wu C (2005) Vessel tree reconstruction in thoracic ct scans with application to nodule detection. IEEE Trans Med Imaging 24: 486–499

    Article  Google Scholar 

  3. Agin GJ, Binford TO (1976) Computer description of curved objects. IEEE Trans on Comput 25(4): 439–449

    Article  MATH  Google Scholar 

  4. Aharinejad S, Schreiner W, Neumann F (1998) Morphometry of human coronary arterial trees. Anat Rec 251: 50–59

    Article  Google Scholar 

  5. Akitaa K, Kugaa H (1982) A computer method of understanding ocular fundus images. Pattern Recogn 15(6): 431–443

    Article  Google Scholar 

  6. Antiga L, Ene-Iordache B, Remuzzi A (2003) Computational geometry for patient-specific reconstruction and meshing of blood vessels from mr and ct angiography. IEEE Trans Med Imaging 22(5): 674–684

    Article  Google Scholar 

  7. Antiga L, Steinman DA (2004) Robust and objective decomposition and mapping of bifurcating vessels. IEEE Trans Med Imaging 23(6): 704–713

    Article  Google Scholar 

  8. Aronovich L, Spiegler I (2010) Bulk construction of dynamic clustered metric trees. Knowl Inf Syst 22(2): 211–244

    Article  Google Scholar 

  9. Aylward SR, Bullitt E (2002) Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction. IEEE Trans Med Imaging 21(2): 61–75

    Article  Google Scholar 

  10. Bezold L (2010, January) Coronary artery anomalies

  11. Bühler K, Felkel P, La Cruz A (2002) Geometric methods for vessel visualization and quantification—a survey. In: Geometric modelling for scientific visualization. Springer, pp 399–420

  12. Blum H (1967) A transformation for extracting new descriptors of shape. In: Wathen-Dunn W (eds) Models for the perception of speech and visual form. MIT Press, Cambridge, pp 362–380

    Google Scholar 

  13. Boskamp T, Rinck D, Link F, Knmmerlen B, Stamm G, Mildenberger P (2004) New vessel analysis tool for morphometric quantification and visualization of vessels in ct and mr imaging datasets. Radiographics 24: 287–297

    Article  Google Scholar 

  14. Bouix S, Siddiqi K, Tannenbaum A (2005) Flux driven automatic centerline extraction. Med Image Anal 9(3): 209–221

    Article  Google Scholar 

  15. Brandes U, Eiglsperger M, Herman I, Himsolt M, Marshall MS (2002) Graphml progress report: structural layer proposal. In: Graph drawing. International symposium No 9, Vienna, LNCS, vol 2265, pp 501–512

  16. Bullitt E, Aylward S, Smith K, Mukherji S, Jiroutek M, Muller K (2001) Symbolic description of intracerebral vessels segmented from magnetic resonance angiograms and evaluation by comparison with x-ray angiograms. Med Image Anal 5: 157–169

    Article  Google Scholar 

  17. Bullitt E, Gerig G, Aylward S, Joshi S, Smith K, Ewend M, Lin W (2003) Vascular attributes and malignant brain tumors. In: Medical image computing and computer-assisted intervention (MICCAI 2003), LNCS, vol 2878. Springer, pp 671–679

  18. Bullitt E, Jung I, Muller K, Gerig G, Aylward S, Joshi S, Smith K, Lin W, Ewend M (2004) Determining malignancy of brain tumors by analysis of vessel shape. In: Medical image computing and computer-assisted intervention (MICCAI 2004), LNCS, vol 3217, pp 645–653

  19. Bullitt E, Muller KE, Jung I, Lin W, Aylward S (2005) Analyzing attributes of vessel populations. Med Image Anal 9: 39–49

    Article  Google Scholar 

  20. Can A, Shen H, Turner JN, Tanenbaum HL, Roysam B (1999) Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms. IEEE Trans Inf Technol Biomed 3: 125–138

    Article  Google Scholar 

  21. Carrillo JF, Hernández-Hoyos M, Dávila-Serrano EE, Orkisz M (2007) Recursive tracking of vascular tree axes in 3d medical images. Int J Comput Assist Radiol Surg 1(6): 331–339

    Article  Google Scholar 

  22. Creager MA, Lüscher TF, Cosentino F, Beckman JA (2003) Diabetes and vascular disease: pathophysiology, clinical consequences, and medical therapy: Part i. Circulation 108: 1527–1532

    Article  Google Scholar 

  23. Cumming G, Harding LK, Horsfield K, Prowse K, Singhal SS, Woldenberg MJ (1970) Morphological aspects of the pulmonary circulation and of the airway. Fluid Dyn Blood Circ Respir Flow 65: 230–236

    Google Scholar 

  24. Deschamps T, Cohen L (2001) Fast extraction of minimal paths in 3d images and applications to virtual endoscopy. Med Image Anal 5(4): 281–299

    Article  Google Scholar 

  25. Dijkstra EW (1959) A note on two problems in connection with graphs. Numer Math 1: 269–271

    Article  MATH  MathSciNet  Google Scholar 

  26. Dos-Reis G, Järvi J (2005) What is generic programming? In: Proceedings of the 1st international workshop of library-centric software design (LCSD’05)

  27. Felkel P, Kanitsar A, Fuhrmann AL, Wegenkittl R (2002) Surface models of tube trees. In: Computer graphics international, pp 70–77

  28. Folkman J (2000) Incipient angiogenesis. J Natl Cancer Inst 92: 94–95

    Article  Google Scholar 

  29. Frangi A, Niessen W, Hoogeveen R, van Walsum T, Viergever M (1999) Model-based quantitation of 3-d magnetic resonance angiographic images. IEEE Trans Med Imaging 18(10): 946–956

    Article  Google Scholar 

  30. Frangi A, Niessen WJ, Nederkoorn PJ, van Elgersma O, Viergever MA (2000) Three-dimensional model-based stenosis quantification of the carotid arteries from contrast-enhanced mr angiography. In: IEEE workshop on mathematical methods in biomedical image analysis

  31. Fridolin I, Lindberg LG (2000) Optical non-invasive technique for vessel imaging: I experimental results. Phys Med Biol 45(12): 3765–3778

    Article  Google Scholar 

  32. Gamma E, Helm R, Johnson R, Vlissides J (2000) Design patterns: elements of reusable object-oriented software. Addison-Wesley, Reading

    Google Scholar 

  33. Gerig G, Koller T, Székely G, Brechbuhler C, Kubler O (1993) Symbolic description of 3d structures applied to cerebral vessel tree obtained from mr angiography volume data. In: Information processing in medical imaging’93, LNCS 687, pp 94–111

  34. Hernández-Hoyos M, Orlowski P, Piatkowska-Janko E, Bogorodzki P, Orkisz M (2006) Vascular centerline extraction in 3d mr angiograms for phase contrast mri blood flow measurement. Int J Comput Assist Radiol Surg 1(1): 51–61

    Article  Google Scholar 

  35. Heron M, Hoyert DL, Murphy SL, Xu J, Kochanek KD, Tejada-Vera B (2009) Deaths: final data for 2006. Report, Division of Vital Statistics, US Dep. of Health and Human Services

  36. Holash J, Maisonpierre PC, Compton D, Boland P, Alexander CR, Zagzag D, Yancopoulos GD, Wiegand SJ (1999) Vessel cooption, regression and growth in tumors mediated by angiopoietins and vegf. Science 284(5422): 1994–1998

    Article  Google Scholar 

  37. Horsfield K (1978) Morphometry of the small pulmonary arteries in man. Circ Res 42: 593–597

    Google Scholar 

  38. Horsfield K (1990) Diameters, generations, and orders of branches in the bronchial tree. J Appl Physiol 68: 457–461

    Google Scholar 

  39. Horsfield K, Gorden I (1981) Morphometry of pulmonary veins in man. Lung 159: 211–218

    Article  Google Scholar 

  40. Huang W, Yen RT, McLaurine M, Bledsoe G (1996) Morphometry of the human pulmonary vasculature. J Appl Physiol 81: 2123–2133

    Google Scholar 

  41. Jain RK (2001) Normalizing tumor vasculature with anti-angiogenic therapy: a new paradigm for combination therapy. Nat Med 7: 987–998

    Article  Google Scholar 

  42. Kang DG, Suh DC, Ra JB (2009) Three-dimensional blood vessel quantification via centerline deformation. IEEE Trans Med Imaging 28(3): 405–414

    Article  Google Scholar 

  43. Karau KL, Krenz GS, Dawson CA (2001) Branching exponent heterogeneity and wall shear stress distribution in vascular trees. AJP Heart Circ Physiol 280: 1256–1263

    Google Scholar 

  44. Kassab GS (2006) Scaling laws of vascular trees: of form and function. AJP Heart Circ Physiol 290: 894–903

    Article  Google Scholar 

  45. Kassab GS, Rider CA, Tang NJ, Fung YC (1993) Morphometry of pig coronary arterial trees. Am J Physiol 265: 350–365

    Google Scholar 

  46. Kirbas C, Quek F (2004) A review of vessel extraction techniques and algorithms. ACM Comput Surv 36(2): 81–121

    Article  Google Scholar 

  47. Klein A, Renema WKJ, Oostveen LJ, Schultze Kool LJ, Slump CH (2008) A segmentation method for stentgrafts in the abdominal aorta from ecg-gated cta data. In: Hu XP, Clough AV (eds) Proceedings of SPIE medical imaging 2008: physiology, function, and structure from medical images, vol 6916

  48. Klein R, Schilling A, Strasser W (1999) Reconstruction and simplification of surfaces from contours. In: Proceedings of 7th Pacific conference on computer graphics and applications

  49. Kok AJF, van Liere R (2007) A multimodal virtual reality interface for 3d interaction with vtk. Knowl Inf Syst 13(2): 197–219

    Article  Google Scholar 

  50. Lange T, Eulenstein S, Huumlnerbein M, Schlag PM (2003) Vessel-based non-rigid registration of mr/ct and 3d ultrasound for navigation in liver surgery. Comput Assist Surg 8(5): 228–240

    Article  Google Scholar 

  51. Lee J, Beighley P, Ritman E, Smith N (2007) Automatic segmentation of 3d micro-ct coronary vascular images. Med Image Anal 11(6): 630–647

    Article  Google Scholar 

  52. Legarreta JH, Boto F, Macía I, Maiora J, García G, Paloc C, Graña M, de Blas M (2010) Hybrid decision support system for endovascular aortic aneurism repair follow-up. In: Proceedings of 5th international conference on hybrid artificial intelligent systems (HAIS’10) (page submitted)

  53. Lesage D, Angelini E, Bloch I, Funka-Lea G (2008) Medial-based bayesian tracking for vascular segmentation: application to coronary arteries in 3d ct angiography. In: IEEE international symposium on biomedical Imaging (ISBI’08), pp 268–271

  54. Lesage D, Angelini ED, Bloch I, Funka-Lea G (2009) A review of 3d vessel lumen segmentation techniques: models, features and extraction schemes. Med Image Anal 13(6): 819–845

    Article  Google Scholar 

  55. Lin Q (2003) Enhancement, extraction and visualization of 3D volume data. PhD thesis, Institute of Technology, Linköpings Universitet

  56. Liu S, Duffy AHB, Whitfield RI, Boyle IM (2009) Integration of decision support systems to improve decision support performance. Knowl Inf Syst 22(3): 261–286

    Article  Google Scholar 

  57. Long B, Zhang Z, Yu PS (2010) A general framework for relation graph clustering. Knowl Inf Syst 24(3): 393–413

    Article  Google Scholar 

  58. Lorensen WE, Cline HE (1987) Marching cubes: a high resolution 3d surface construction algorithm. Comput Graph 21(4): 163–169

    Article  Google Scholar 

  59. Lorigo LM, Faugeras O, Grimson WEL, Keriven R, Kikinis R, Westin CF (1999) Co-dimension 2 geodesic active contours for mra segmentation. In: IPMI, pp 126–139

  60. de Bruijne MM, van Ginneken B, Niessen WJ, Loog M, Viergever M (2003) Model-based segmentation of abdominal aortic aneurysms in cta images. In: Proceedings of SPIE medical imaging, vol 5032, pp 1560–1571

  61. Macía I, Graña M, Paloc C, Boto F (2010) Neural network-based detection of type ii endoleaks in cta images after endovascular repair. Comput Biol Med (page submitted)

  62. Macía I, Legarreta JH, Paloc C, Graña M, Maiora J, García G, de Blas M (2009) Segmentation of abdominal aortic aneurysms in ct images using a radial model approach. In: Corchado E, Yin H (eds) Proceedings of intelligent data engineering and automated learning, 10th international conference (IDEAL’09), vol 5788 of Lecture Notes in Computer Science (LNCS). Springer, Burgos Spain, pp 664–671

  63. Macía I, Wald D, Paloc C (2008) Extraction and analysis of patient-specific hepatic anatomy from mr images. In: Int J Comput Assist Radiol Surg. Proceedings of the 22nd international congress and exhibition (CARS’08), Barcelona, vol Suppl. 1, pp 399–401

  64. Maiora J, García G, Macía I, Legarreta JH, Boto F, Paloc C, Graña M, Sánchez J (2010) Thrombus volume change visualization after endovascular abdominal aortic aneurysm repair. In: Proceedings of 5th international conference on hybrid artificial intelligent systems (HAIS’10) (page submitted)

  65. Maiora J, García G, Macía I, Legarreta JH, Paloc C, de Blas M, Graña M (2010) Thrombus change detection after endovascular abdominal aortic aneurysm repair. In: Proceedings of computer assisted radiology and surgery (CARS’10) (page in press)

  66. Maiora J, García G, Tapia A, Macía I, Legarreta JH, Paloc C, Graña M, de Blas M (2009) Stent graft change detection after endovascular abdominal aortic aneurysm repair. In: Corchado E, Yin H (eds) Intelligent data engineering and automated learning—IDEAL 2009 10th international conference, proceedings, vol 5788 of Lecture Notes in Computer Science (LNCS), p 826, Universidad de Burgos, Burgos, Spain. Springer

  67. Martin K, Hoffman B (2008) Mastering CMake, 4th edn. Kitware Inc., USA

    Google Scholar 

  68. Metzena JH, Krögerb T, Schenk A, Zidowitz S, Peitgen HO, Jiang X (2009) Matching of anatomical tree structures for registration of medical images. Image Vis Comput 27(7): 923–933

    Article  Google Scholar 

  69. Mille J, Cohen LD (2009) Deformable tree models for 2d and 3d branching structures extraction. In: IEEE conference on computer vision and pattern recognition workshops

  70. Millán RD, Dempere-Marco L, Pozo JM, Cebral JR, Frangi AF (2007) Morphological characterization of intracranial aneurysms using 3-d moment invariants. IEEE Trans Med Imaging 26(9): 1270–1282

    Article  Google Scholar 

  71. Miyazaki M, Ichinose N, Sugiura S, Kanazawa H, Machida Y, Kassai Y (2005) A novel mr angiography technique: speed acquisition using half-fourier rare. J Magn Reson Imaging 8(2): 505–507

    Article  Google Scholar 

  72. Murray C (1926) The physiological principle of minimum work, i: the vascular system and the cost of blood volume. Proc Natl Acad Sci USA 12(3): 207–214

    Article  Google Scholar 

  73. Näf M (1996) 3D Voronoi Skeletons: a Semicontinuous Implementation of the ’Symmetric Axis Transform’ in 3D Space. PhD thesis, ETH Zürich

  74. Nilsson O, Breen D, Museth K (2005) Surface reconstruction via contour metamorphosis: an eulerian approach with lagrangian particle tracking. In: Proceedings of 16th IEEE visualization (VIS’05)

  75. Nordsletten DA, Blackett S, Bentley MD, Ritman EL, Smith NP (2006) Structural morphology of renal vasculature. AJP Heart Circ Physiol 291: 296–309

    Article  Google Scholar 

  76. O’Donnell T, Boult T, Fang X, Gupta A (1994) The extruded generalized cylinder: a deformable model for object recovery. In: Proceedings of computer vision and pattern recognition (CVPR’94), pp 174–181

  77. Oka S, Nakai M (1987) Optimality principle in vascular bifurcation. Biorheology 24(6): 737–751

    Google Scholar 

  78. Olabarriaga S, Breeuwer M, Niessen WJ (2003) Minimum cost path algorithm for coronary artery central axis tracking in ct images. In: Medical image computing and computer assisted intervention (MICCAI’03)

  79. Orkisz M, Flórez-Valencia L, Hernández-Hoyos M (2008) Models, algorithms and applications in vascular image segmentation. Mach Graph Vis 17(1/2): 5–33

    Google Scholar 

  80. Osher S, Sethian JA (1988) Fronts propagating with curvature-dependent speed: algorithms based on hamilton-jacobi formulations. J Comput Phys 79: 12–49

    Article  MATH  MathSciNet  Google Scholar 

  81. Palágyi K, Sorantin E, Balogh E, Kuba A, Halmai C, Erdohelyi B, Hausegger K (2001) A sequential 3d thinning algorithm and its medical applications. In: Proceedings of the 17th international conference on information processing in medical imaging (IPMI’01), LNCS, vol 2082. Springer, pp 409–415

  82. Paradowski M, Kwasnicka H, Borysewicz K (2009) Capillary blood vessel tortuosity measurement using graph analysis. In: Knowledge-based and intelligent information and engineering systems, 13th international conference (KES 2009)

  83. Park J, Lee S (2010) Keyword search in relational databases. Knowl Inf Syst (in print)

  84. Piccinelli M, Veneziani A, Steinman DA, Remuzzi A, Antiga L (2009) A framework for geometric analysis of vascular structures: application to cerebral aneurysms. Trans Med Imaging 28(8): 1141–1155

    Article  Google Scholar 

  85. Pizer SM, Eberly D, Morse BS, Fritsch DS (1998) Zoom-invariant figural shape: the mathematics of cores. Comput Vis Image Underst 69: 55–71

    Article  Google Scholar 

  86. Pizer SM, Siddiqi K, Székely G, Damon JN, Zucker SW (2003) Multi-scale medial loci and their properties. Int J Comput Vis 55(2–3): 155–179

    Article  Google Scholar 

  87. Pock T, Janko C, Beichel R, Bischof H (2005) Multiscale medialness for robust segmentation of 3d tubular structures. In: 10th Computer vision winter workshop

  88. Puig A, Tost D, Navazo I (2000) Hybrid model for vascular tree structures. In: van Leeuw LR, de W (eds) Data visualization 2000: joint eurographics and IEEE TCVG symposium on visualization, Amsterdam. Springer, Berlin, pp 125–135

    Google Scholar 

  89. Quek FKH, Kirbas C (2001) Vessel extraction in medical images by wave-propagation and traceback. IEEE Trans Med Imaging 20(2): 117–131

    Article  Google Scholar 

  90. Reichenbach JR, Venkatesan R, Schillinger DJ, Kido DK, Haacke EM (1997) Small vessels in the human brain: Mr venography with deoxyhemoglobin as an intrinsic contrast agent. Radiology 204: 272–277

    Google Scholar 

  91. Ritman EL (2005) Micro-computed tomography of the lungs and pulmonary-vascular system. Proc Am Thorac Soc 2: 477–480

    Article  Google Scholar 

  92. Sangalli LM, Vantini S (2008) Registration of functional data: aligning inner carotid artery centerlines. In: Proceedings of the XLIV Riunione Scientifica Società Italiana di Statistica

  93. Santamore WP, Bove AA (2008) Why arteries are the size they are. J Appl Physiol 104: 1259

    Article  Google Scholar 

  94. Schaap M, Metz CT, van Walsum T, van der Giessen AG, Weustink AC, Mollet NR, Bauer C, Bogunovic H, Castro C, Deng X, Dikici E, O’Donnell T, Frenay M, Friman O, Hernández Hoyos M, Kitslaar PH, Krissian K, Kühnel C, Luengo-Oroz MA, Orkisz M, Smedby Ö, Styner M, Szymczak A, Tek H, Wang C, Warfield SK, Zhang Y, Zambal S, Krestin GP, Niessen WJ (2009) Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms. Med Image Anal 13(5): 701–714

    Article  Google Scholar 

  95. Schroeder W, Martin K, Lorensen B (2006) The visualization toolkit: an object-oriented approach to 3D graphics, 4th edn. Kitware, Clifton Park

    Google Scholar 

  96. Schwarz M, Nguyen MP, Kiencke U, Heilmann C, Klemm R, Benk C, Beyersdorf F, Busch HJ (2008) Integration of the circle of willis into avolio’s model of the arterial hemodynamics. In: 6th IASTED international conference on biomedical engineering

  97. Selle D, Preim B, Schenk A, Peitgen HO (2002) Analysis of vasculature for liver surgical planning. IEEE Trans Med Imaging 21: 1344–1357

    Article  Google Scholar 

  98. Sherman TF (1981) On connecting large vessels to small: the meaning of Murray’s law. J Gen Physiol 78: 431–453

    Article  Google Scholar 

  99. Siddiqi K, Kimia BB (1996) A shock grammar for recognition. cvpr’96:507–513, san francisco, ca, ieee. In: IEEE computer vision and pattern recognition (CVPR’96), pp 507–513

  100. Siddiqi K, Pizer S (2008) Medial representations: mathematics, algorithms and applications. Springer, ISBN 978-1402086571

  101. Singhal S, Henderson R, Horsfield K, Harding K, Cumming G (1973) Morphometry of the human pulmonary arterial tree. Circ Res 33: 190–197

    Google Scholar 

  102. Sones FM, Shirey EK (1962) Cine coronary arteriography. Mod Concepts Cardiovasc Dis 31: 735–738

    Google Scholar 

  103. Strahler AN (1952) Hypsometric (area-altitude) analysis of erosional topology. Geol Soc Am Bull 63(11): 1117–1142

    Article  Google Scholar 

  104. Torii R, Oshima M, Kobayashi T, Takagi K, Tezduyar TE (2007) Influence of wall elasticity in patient-specific hemodynamic simulations. Comput Fluids 36(1): 160–168

    Article  MATH  Google Scholar 

  105. van Bemmel C, Wink O, Verdonck B, Viergever M, Niessen W (2003) Blood pool contrast-enhanced mra: improved arterial visualization in the steady state. IEEE Trans Med Imaging 22(5): 645–652

    Article  Google Scholar 

  106. van Herzeele I, Aggarwal R, Malik I (2009) Use of simulators in vascular training. Heart 95: 613–614

    Article  Google Scholar 

  107. van Ooijen PMA, de Jonge G, Oudkerk M (2007) Coronary fly-through or virtual angioscopy using dual-source mdct data. Eur Radiol 17(11): 2852–2859

    Article  Google Scholar 

  108. Vukadinovic D, van Walsum T, Manniesing R, Rozie S, Hameeteman R, de Weert TT, van der Lugt A, Niessen WJ (2010) Segmentation of the outer vessel wall of the common carotid artery in cta. IEEE Trans 29(1): 65–76

    Google Scholar 

  109. Wang S, Chen J, Yang X, Zhang X (2008) Patient-specific hemodynamic analysis for cerebral aneurysm. In: Proceedings of 2nd international conference on bioinformatics and biomedical engineering (ICBBE’08)

  110. Wilson CM, Cocker KD, Moseley MJ, Paterson C, Clay ST, Schulenburg WE, Mills MD, Ells AL, Parker KH, Quinn GE, Fielder AR, Ng J (2008) Computerized analysis of retinal vessel width and tortuosity in premature infants. Investig Ophthalmol Vis Sci 49(8): 3577–3585

    Article  Google Scholar 

  111. Wink O, Niessen WJ, Viergever MA (2004) Multiscale vessel tracking. IEEE Trans Med Imaging 23(1): 130–133

    Article  Google Scholar 

  112. Wischgoll T, Choy JS, Kassab GS (2009) Extraction of morphometry and branching angles of porcine coronary arterial tree from ct images. AJP Heart Circ Physiol 297: 1949–1955

    Article  Google Scholar 

  113. Witt N, Wong TY, Hughes AD, Chaturvedi N, Klein BE, Evans R, McNamara M, Thom SAM, Klein R (2006) Abnormalities of retinal microvascular structure and risk of mortality from ischemic heart disease and stroke. Hypertension 47: 975–981

    Article  Google Scholar 

  114. Woodrum DA, Romano AJ, Lerman A, Pandya UH, Brash D, Rossman PJ, Lerman LO, Ehman RL (2006) Vascular wall elasticity measurement by magnetic resonance imaging. Magn Reson Med 56: 593–600

    Article  Google Scholar 

  115. Worz S, Rohr K (2007) Segmentation and quantification of human vessels using a 3-d cylindrical intensity model. IEEE Trans Image Process 16(8): 1994–2004

    Article  MathSciNet  Google Scholar 

  116. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, Motoda H, McLachlan GJ, Ng A, Liu B, Yu PS, Zhou ZH, Steinbach M, Hand DJ, Steinberg D (2008) Top 10 algorithms in data mining. Knowl Inf Syst 14(1): 1–37

    Article  Google Scholar 

  117. Yang J, Yu LX, Rennie MY, Sled JG, Henkelman RM (2010) Comparative structural and hemodynamic analysis of vascular trees. AJP Heart Circ Physiol 298: 1249–1259

    Article  Google Scholar 

  118. Yang Q, Liu J, Barnes SRS, Wu Z, Li K, Neelavalli J, Hu J, Haacke EM (2009) Imaging the vessel wall in major peripheral arteries using susceptibility-weighted imaging. J Magn Reson Imaging 30(2): 357–365

    Article  Google Scholar 

  119. Yoo TS, Ackerman MJ, Lorensen WE, Schroeder W, Chalana V, Aylward S, Metaxas D, Whitaker R (2002) Engineering and algorithm design for an image processing api: a technical report on itk—the insight toolkit. Stud Health Technol Inf 85: 586–592

    Google Scholar 

  120. Zhou L, Rzeszotarski MS, Singerman LJ, Chokreff JM (1994) The detection and quantification of retinopathy using digital angiogram. IEEE Trans Med Imaging 13: 619–626

    Article  Google Scholar 

  121. Zhou Y, Kassab GS, Molloi S (1999) On the design of the coronary arterial tree: a generalization of Murray’s law. Phys Med Biol 44: 2929–2945

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Vicomtech, Visual Communications Technologies Centre, San Sebastian, Spain

    Iván Macía & Celine Paloc

  2. Grupo de Inteligencia Computacional, UPV/EHU, San Sebastian, Spain

    Manuel Graña

Authors
  1. Iván Macía
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manuel Graña
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Celine Paloc
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Manuel Graña.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Macía, I., Graña, M. & Paloc, C. Knowledge management in image-based analysis of blood vessel structures. Knowl Inf Syst 30, 457–491 (2012). https://doi.org/10.1007/s10115-010-0377-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10115-010-0377-x

Keywords

Search

Navigation