Skip to main content
SpringerLink
Log in

Computational Human Models in Cardiovascular Imaging: From Design to Generations

  • Chapter
  • First Online:
Cardiovascular Engineering

Part of the book series: Series in BioEngineering ((SERBIOENG))

  • 730 Accesses

Abstract

Computational human models have evolved into important tools in simulating various sets of cardiovascular circumstances to support the understanding, diagnosis, and treatment of diseases. The involvement of cardiac imaging in cardiac models have shown great improvement in representing the anatomy and physiology of the heart, not only with better functions, but also equipped with more realistic geometrical and structural features. In consort with the advancements of computing and imaging methods, different types of cardiac models have also been built in large range of applications and purposes. The implementations of most cardiac models are mainly referred to the general computational human model types, from Stylized, Voxelized, to Boundary representation (BREP) models, from the whole heart to partial cardiac regions, and from single to multiple cardiac applications. These wide range of cardiac models are interesting to analyze as a part of learning process, model improvements, and application adaptation. This chapter reviews the development of generations in computational human models for cardiovascular applications. The objective of this review is to map the state-of-the-art in the development of computational human models in cardiovascular applications. The review highlights on the uses of different types of computational human model approaches, the evolution of cardiac models in various anthropometry, as well as the advancements of computational models as whole and partial regions of the heart. Some technical hints are also elaborated to provide brief understanding on the development process of cardiac models.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Xu, X.G., Eckerman, K.F. (eds.): Handbook of Anatomical Models for Radiation Dosimetry. CRC press (2009)

    Google Scholar 

  2. Zaidi, H., Tsui, B.M.: Review of computational anthropomorphic anatomical and physiological models. Proc. IEEE 97(12), 1938–1953 (2009)

    Article  Google Scholar 

  3. Hunter, P., Nielsen, P.: A strategy for integrative computational physiology. Physiology 20(5), 316–325 (2005)

    Article  Google Scholar 

  4. Trayanova, N.A.: Whole-heart modeling: applications to cardiac electrophysiology and electromechanics. Circ. Res. 108(1), 113–128 (2011)

    Article  Google Scholar 

  5. Lopez-Perez, A., Sebastian, R., Ferrero, J.M.: Three-dimensional cardiac computational modelling: methods, features and applications. Biomed. Eng. Online 14(1), 35 (2015)

    Article  Google Scholar 

  6. Antiga, L., Piccinelli, M., Botti, L., Ene-Iordache, B., Remuzzi, A., Steinman, D.A.: An image-based modeling framework for patient-specific computational hemodynamics. Med. Biol. Eng. Comput. 46(11), 1097 (2008)

    Article  Google Scholar 

  7. Clark, D.E., Pickett, S.D.: Computational methods for the prediction of ‘drug-likeness’. Drug Discov. Today 5(2), 49–58 (2000)

    Article  Google Scholar 

  8. DeWerd, L.A.: The Phantoms of Medical and Health Physics. M. Kissick (ed.). Springer, New York (2014)

    Google Scholar 

  9. Ayache, N., Lions, J.L. (eds.): Computational Models for the Human Body, vol. 12. Gulf Professional Publishing (2004)

    Google Scholar 

  10. Metaxas, D.N.: Physics-Based Deformable Models: Applications to Computer Vision, Graphics and Medical Imaging, vol. 389. Springer, New York (2012)

    Google Scholar 

  11. Henriet, J., Leni, P.E., Laurent, R., Salomon, M.: Case-based reasoning adaptation of numerical representations of human organs by interpolation. Expert Syst. Appl. 41(2), 260–266 (2014)

    Article  Google Scholar 

  12. Lee, L.C., Genet, M., Dang, A.B., Ge, L., Guccione, J.M., Ratcliffe, M.B.: Applications of computational modeling in cardiac surgery. J. Card. Surg. Incl. Mech. Biol. Support Heart Lungs 29(3), 293–302 (2014)

    Google Scholar 

  13. Sermesant, M., Delingette, H., Ayache, N.: An electromechanical model of the heart for image analysis and simulation. IEEE Trans. Med. Imag. 25(5), 612–625 (2006)

    Article  Google Scholar 

  14. Kim, H.J., Vignon-Clementel, I.E., Coogan, J.S., Figueroa, C.A., Jansen, K.E., Taylor, C.A.: Patient-specific modeling of blood flow and pressure in human coronary arteries. Ann. Biomed. Eng. 38(10), 3195–3209 (2010)

    Article  Google Scholar 

  15. Clayton, R.H., Bernus, O., Cherry, E.M., Dierckx, H., Fenton, F.H., Mirabella, L., Panfilov, A.V., Sachse, F.B., Seemann, G., Zhang, H.: Models of cardiac tissue electrophysiology: progress, challenges and open questions. Prog. Biophys. Mol. Biol. 104(1–3), 22–48 (2011)

    Article  Google Scholar 

  16. Wong, J., Kuhl, E.: Generating fibre orientation maps in human heart models using Poisson interpolation. Comput. Methods Biomech. Biomed. Eng. 17(11), 1217–1226 (2014)

    Article  Google Scholar 

  17. Dössel, O., Krueger, M.W., Weber, F.M., Wilhelms, M., Seemann, G.: Computational modeling of the human atrial anatomy and electrophysiology. Med. Biol. Eng. Comput. 50(8), 773–799 (2012)

    Article  Google Scholar 

  18. Deng, D., Jiao, P., Ye, X., Xia, L.: An image-based model of the whole human heart with detailed anatomical structure and fiber orientation. Comput. Math. Methods Med. 2012, 1–16 (2012)

    Article  MathSciNet  Google Scholar 

  19. Verkerke, G.J., Houwen, E.V.D.: Design of biomedical products. In: Biomaterials in Modern Medicine: The Groningen Perspective, pp. 23–38 (2008)

    Chapter  Google Scholar 

  20. Völter, M., Stahl, T., Bettin, J., Haase, A., Helsen, S.: Model-Driven Software Development: Technology, Engineering, Management. Wiley, London (2013)

    Google Scholar 

  21. Shefelbine, S., Clarkson, P. J., Farmer, R.: Good design practice for medical devices and equipment-requirements capture (2002)

    Google Scholar 

  22. Xu, X.G.: An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: a review of the fifty-year history. Phys. Med. Biol. 59(18), R233 (2014)

    Article  Google Scholar 

  23. Grenander, U., Miller, M.I.: Computational anatomy: an emerging discipline. Q. Appl. Math. 56(4), 617–694 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  24. Dingreville, R., Karnesky, R.A., Puel, G., Schmitt, J.H.: Review of the synergies between computational modeling and experimental characterization of materials across length scales. J. Mater. Sci. 51(3), 1178–1203 (2016)

    Article  Google Scholar 

  25. Ottesen, J.T., Olufsen, M.S., Larsen, J.K.: Applied Mathematical Models in Human Physiology. Society for Industrial and Applied Mathematics (2004)

    Google Scholar 

  26. Jerby, L., Shlomi, T., Ruppin, E.: Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism. Mol. Syst. Biol. 6(1), 401 (2010)

    Article  Google Scholar 

  27. O’reilly, R.C.: Biologically based computational models of high-level cognition. Science 314(5796), 91–94 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  28. Frances, A., Sandra, O., Lucy, U.: Vascular cognitive impairment, a cardiovascular complication. World J. Psychiatry 6(2), 199 (2016)

    Article  Google Scholar 

  29. Brodland, G.W.: How computational models can help unlock biological systems. In: Seminars in Cell & Developmental Biology, vol. 47, pp. 62–73. Academic Press (2015, December)

    Google Scholar 

  30. Wronecki, J.: Concept modeling with NURBS, polygon and subdivision surfaces. In: Proceedings of the 2006 American Society for Engineering Education Annual Conference & Exposition (2006)

    Google Scholar 

  31. Wilhelms, J., Van Gelder, A.: Anatomically based modeling. In: Proceedings of the 24th annual conference on Computer Graphics and Interactive Techniques, pp. 173–180. ACM Press/Addison-Wesley Publishing Co. (1997, August)

    Google Scholar 

  32. Yang, Y.J., Cao, S., Yong, J.H., Zhang, H., Paul, J.C., Sun, J.G., Gu, H.J.: Approximate computation of curves on B-spline surfaces. Comput.-Aided Des. 40(2), 223–234 (2008)

    Article  Google Scholar 

  33. Gibson, S.F., Mirtich, B.: A survey of deformable modeling in computer graphics. Technical Report, Mitsubishi Electric Research Laboratories (1997)

    Google Scholar 

  34. Prautzsch, H., Boehm, W., Paluszny, M.: Bézier and B-spline techniques. Springer, New York (2013)

    Google Scholar 

  35. Yoo, D.J.: Three-dimensional surface reconstruction of human bone using a B-spline based interpolation approach. Comput.-Aided Des. 43(8), 934–947 (2011)

    Article  Google Scholar 

  36. Botsch, M., Pauly, M., Kobbelt, L., Alliez, P., Lévy, B., Bischoff, S., Röossl, C.: Geometric modeling based on polygonal meshes (2007)

    Google Scholar 

  37. Cassola, V. F., de Melo Lima, V. J., Kramer, R., Khoury, H. J.: FASH and MASH: female and male adult human phantoms based on polygon mesh surfaces: I. Development of the anatomy. Phys. Med. Biol. 55(1), 133 (2009)

    Article  Google Scholar 

  38. Wellstead, P.E.: Introduction to Physical System Modelling, pp. 17–32. Academic Press, London (1979)

    Google Scholar 

  39. Sherwin, S.J., Formaggia, L., Peiro, J., Franke, V.: Computational modelling of 1D blood flow with variable mechanical properties and its application to the simulation of wave propagation in the human arterial system. Int. J. Numer. Methods Fluids 43(6–7), 673–700 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  40. Steinman, D.A.: Image-based computational fluid dynamics modeling in realistic arterial geometries. Ann. Biomed. Eng. 30(4), 483–497 (2002)

    Article  Google Scholar 

  41. Sørensen, D.N., Voigt, L.K.: Modelling flow and heat transfer around a seated human body by computational fluid dynamics. Build. Environ. 38(6), 753–762 (2003)

    Article  Google Scholar 

  42. Duffy, V.G.: Handbook of Digital Human Modeling: Research for Applied Ergonomics and Human Factors Engineering. CRC press (2016)

    Google Scholar 

  43. Fiala, D., Havenith, G.: Modelling human heat transfer and temperature regulation. In: The Mechanobiology and Mechanophysiology of Military-Related Injuries, pp. 265–302. Springer, Cham (2015)

    Google Scholar 

  44. Bhatti, M.M., Zeeshan, A., Ellahi, R.: Heat transfer analysis on peristaltically induced motion of particle-fluid suspension with variable viscosity: clot blood model. Comput. Methods Prog. Biomed. 137, 115–124 (2016)

    Article  Google Scholar 

  45. Wessapan, T., Srisawatdhisukul, S., Rattanadecho, P.: Specific absorption rate and temperature distributions in human head subjected to mobile phone radiation at different frequencies. Int. J. Heat Mass Transfer 55(1–3), 347–359 (2012)

    Article  MATH  Google Scholar 

  46. Zaidi, H., Xu, X.G.: Computational anthropomorphic models of the human anatomy: the path to realistic Monte Carlo modeling in radiological sciences. Annu. Rev. Biomed. Eng. 9, 471–500 (2007)

    Article  Google Scholar 

  47. Zaidi, H.: Relevance of accurate Monte Carlo modeling in nuclear medical imaging. Med. Phys. 26(4), 574–608 (1999)

    Article  Google Scholar 

  48. Kroese, D.P., Brereton, T., Taimre, T., Botev, Z.I.: Why the Monte Carlo method is so important today. Wiley Interdiscip. Rev. Comput. Stat. 6(6), 386–392 (2014)

    Article  Google Scholar 

  49. Schultz, F.W., Geleijns, J., Spoelstra, F.M., Zoetelief, J.: Monte Carlo calculations for assessment of radiation dose to patients with congenital heart defects and to staff during cardiac catheterizations. Br. J. Radiol. 76(909), 638–647 (2003)

    Article  Google Scholar 

  50. Mollemans, W., Schutyser, F., Van Cleynenbreugel, J., Suetens, P.: Tetrahedral mass spring model for fast soft tissue deformation. In: Surgery Simulation and Soft Tissue Modeling, pp. 145–154. Springer, Berlin, Heidelberg (2003)

    Chapter  Google Scholar 

  51. Mohr, M.B., Blümcke, L.G., Seemann, G., Sachse, F.B., Dössel, O.: Volume modeling of myocardial deformation with a spring mass system. In: Surgery Simulation and Soft Tissue Modeling, pp. 332–339. Springer, Berlin, Heidelberg (2003)

    Chapter  Google Scholar 

  52. Hammer, P.E., Sacks, M.S., Pedro, J., Howe, R.D.: Mass-spring model for simulation of heart valve tissue mechanical behavior. Ann. Biomed. Eng. 39(6), 1668–1679 (2011)

    Article  Google Scholar 

  53. Votta, E., Le, T.B., Stevanella, M., Fusini, L., Caiani, E.G., Redaelli, A., Sotiropoulos, F.: Toward patient-specific simulations of cardiac valves: state-of-the-art and future directions. J. Biomech. 46(2), 217–228 (2013)

    Article  Google Scholar 

  54. Tavassoly, I., Goldfarb, J., Iyengar, R.: Systems biology primer: the basic methods and approaches. Essays Biochem. 62(4), 487–500 (2018)

    Article  Google Scholar 

  55. Kitano, H.: Computational systems biology. Nature 420(6912), 206 (2002)

    Article  Google Scholar 

  56. Brusic, V., Zeleznikow, J.: Knowledge discovery and data mining in biological databases. Knowl. Eng. Rev. 14(3), 257–277 (1999)

    Article  Google Scholar 

  57. Toni, T., Stumpf, M.P.: Simulation-based model selection for dynamical systems in systems and population biology. Bioinformatics 26(1), 104–110 (2009)

    Article  Google Scholar 

  58. Borenstein, E.: Computational systems biology and in silico modeling of the human microbiome. Brief. Bioinform. 13(6), 769–780 (2012)

    Article  Google Scholar 

  59. Hunter, P., Chapman, T., Coveney, P.V., De Bono, B., Diaz, V., Fenner, J., Frangi, A.F., Harris, P., Hose, R., Kohl, P., Lawford, P.: A vision and strategy for the virtual physiological human: 2012 update. Interface Focus 3(2), 20130004 (2013)

    Article  Google Scholar 

  60. Viceconti, M., Hunter, P.: The virtual physiological human: ten years after. Ann. Rev. Biomed. Eng. 18, 103–123 (2016)

    Article  Google Scholar 

  61. Hoekstra, A.G., van Bavel, E., Siebes, M., Gijsen, F., Geris, L.: Virtual physiological human 2016: translating the virtual physiological human to the clinic (2017)

    Article  Google Scholar 

  62. Azuaje, F., Devaux, Y., Wagner, D.: Computational biology for cardiovascular biomarker discovery. Briefings Bioinform. 10(4), 367–377 (2009)

    Article  Google Scholar 

  63. Smith, N.P., Crampin, E.J., Niederer, S.A., Bassingthwaighte, J.B., Beard, D.A.: Computational biology of cardiac myocytes: proposed standards for the physiome. J. Exp. Biol. 210(9), 1576–1583 (2007)

    Article  Google Scholar 

  64. Sun, R.: Introduction to computational cognitive modeling. In: Cambridge Handbook of Computational Psychology, pp. 3–19 (2008)

    Google Scholar 

  65. Bechtel, W., Graham, G., Balota, D.A. (eds.): A Companion to Cognitive Science, pp. 1–104. Blackwell, Oxford (1998)

    Google Scholar 

  66. Winslow, R.L., Trayanova, N., Geman, D., Miller, M.I.: Computational medicine: translating models to clinical care. Sci. Transl. Med. 4(158), 158rv11 (2012)

    Article  Google Scholar 

  67. Hamburg, M.A., Collins, F.S.: The path to personalized medicine. N. Engl. J. Med. 363(4), 301–304 (2010)

    Article  Google Scholar 

  68. Neufeld, E., Lloyd, B., Kainz, W., Kuster, N.: Functionalized anatomical models for computational life sciences. Front. Physiol. 9, 1594 (2018)

    Article  Google Scholar 

  69. Schank, R.C., Abelson, R.P.: Scripts, Plans, Goals, and Understanding: An Inquiry into Human Knowledge Structures. Psychology Press (2013)

    Google Scholar 

  70. Taylor, R.H., Menciassi, A., Fichtinger, G., Fiorini, P., Dario, P.: Medical robotics and computer-integrated surgery. In: Springer Handbook of Robotics, pp. 1657–1684. Springer, Cham (2016)

    Chapter  Google Scholar 

  71. Valentin, J.: Basic anatomical and physiological data for use in radiological protection: reference values: ICRP Publication 89. Ann. ICRP 32(3–4), 1–277 (2002)

    Article  Google Scholar 

  72. Williams, G., Swanson, W.P., Kragh, P., Drexler, G.: Calculation and analysis of photon dose equivalent distributions in the ICRU sphere (No. GSF-S–958). Gesellschaft fuer Strahlen-und Umweltforschung mbH Muenchen (1983)

    Google Scholar 

  73. Fisher, H.L.J. Snyder, W.S.: Variation of dose delivered by 137Cs as a function of body size from infancy to adulthood. ORNL-4007. Oak Ridge National Laboratory, Oak Ridge, TN, pp. 221 (1966)

    Google Scholar 

  74. Snyder, W.S., Ford, M.R., Warner, G.G.: MIRD Pamphlet No. 5, Revised Estimates of specific absorbed fractions for monoenergetic photon sources uniformly distributed in various organs of a heterogeneous phantom. Society of Nuclear Medicine, New York (1978)

    Google Scholar 

  75. Kramer, R., Zankl, M., Williams, G., Drexler, G.: The Calculation of Dose from External Photon Exposures Using Reference Human Phantoms and Monte Carlo Methods: Part I. The Male (ADAM) and Female (EVA) Adult Mathematical Phantoms GSF-Report S-885. Institut fuer Strahlenschutz, GSF-Forschungszentrum fuer Umwelt und Gesundheit, Neuherberg (1982)

    Google Scholar 

  76. Billings, M.P., Yucker, W.R.: The computerized anatomical man CAM model, NASA CR-134043. Government Printing Office, Washington, DC (1973)

    Google Scholar 

  77. Tsui, B.M.W., Terry, J.A., Gullberg, G.T.: Evaluation of cardiac cone-beam single-photon emission computed-tomography using observer performance experiments and receiver operating characteristic analysis. Invest. Radiol. 28, 1101 (1993)

    Article  Google Scholar 

  78. Segars, W.P., Tsui, B.M.: MCAT to XCAT: the evolution of 4-D computerized phantoms for imaging research: computer models that take account of body movements promise to provide evaluation and improvement of medical imaging devices and technology. Proc. IEEE (Institute of Electrical and Electronics Engineers) 97(12), 1954 (2009)

    Article  Google Scholar 

  79. Peter, J., Tornai, M.P., Jaszczak, R.J.: Analytical versus voxelized phantom representation for Monte Carlo simulation in radiological imaging. IEEE Trans. Med. Imag. 19(5), 556–564 (2000)

    Article  Google Scholar 

  80. Segars, W.P., Lalush, D.S., Tsui, B.M.: Modeling respiratory mechanics in the MCAT and spline-based MCAT phantoms. IEEE Trans. Nucl. Sci. 48(1), 89–97 (2001)

    Article  Google Scholar 

  81. Kaufman, A.: Voxels as a computational representation of geometry. The computational representation of geometry. SIGGRAPH 94, 45 (1994)

    Google Scholar 

  82. Zubal, I.G., Harrell, C.R., Smith, E.O., Rattner, Z., Gindi, G., Hoffer, P.B.: Computerized three-dimensional segmented human anatomy. Med. Phys. 21(2), 299–302 (1994)

    Article  Google Scholar 

  83. Law, M.Y., Liu, B.: DICOM-RT and its utilization in radiation therapy. Radiographics 29(3), 655–667 (2009)

    Article  Google Scholar 

  84. Pinter, C., Lasso, A., Wang, A., Jaffray, D., Fichtinger, G.: SlicerRT: radiation therapy research toolkit for 3D Slicer. Med. Phys. 39(10), 6332–6338 (2012)

    Article  Google Scholar 

  85. Caon, M.: Voxel-based computational models of real human anatomy: a review. Radiat. Environ. Biophys. 42(4), 229–235 (2004)

    Article  Google Scholar 

  86. Gibbs, S., Pujol, J.: A Monte Carlo method for patient dosimetry from diagnostic x-ray. Dentomaxillofac Radiol. 11, 25 (1982)

    Article  Google Scholar 

  87. Gibbs, S.J., Pujol Jr., A., Chen, T.S., Carlton, J.C., Dosmann, M.A., Malcolm, A.W., James Jr., A.E.: Radiation doses to sensitive organs from intraoral dental radiography. Dentomaxillofacial Radiol. 16(2), 67–77 (1987)

    Article  Google Scholar 

  88. Valentin, J.: Basic anatomical and physiological data for use in radiological protection: reference values: ICRP Publication 89. Ann. ICRP 32(3–4), 1–277 (2002)

    Article  Google Scholar 

  89. Valentin, J.: The 2007 recommendations of the international commission on radiological protection, pp. 1–333. Elsevier, Oxford (2007)

    Google Scholar 

  90. World Health Organization. Extremely low frequency fields (2007)

    Google Scholar 

  91. Sjogreen, K.: The Zubal Phantom Data, Voxel-Based Anthropomorphic Phantoms. http://noodle.med.yale.edu/phantom (1998)

  92. Zankl, M., Wittmann, A.: The adult male voxel model “Golem” segmented from whole-body CT patient data. Radiat. Environ. Biophys. 40, 153–162 (2001)

    Article  Google Scholar 

  93. Caon, M., Bibbo, G., Pattison, J.: An EGS4-ready tomographic computational model of a 14-year-old female torso for calculating organ doses from CT examinations. Phys. Med. Biol. 44, 2213–2225 (1999)

    Article  Google Scholar 

  94. Caon, M., Bibbo, G., Pattison, J.: Monte Carlo calculated effective dose to teenage girls from computed tomography examinations. Radiat. Prot. Dosim. 90(4), 445–448 (2000)

    Article  Google Scholar 

  95. Caon, M., Sedlář, J., Bajger, M., Lee, G.: Computer-assisted segmentation of CT images by statistical region merging for the production of voxel models of anatomy for CT dosimetry. Australas. Phys. Eng. Sci. Med. 37(2), 393–403 (2014)

    Article  Google Scholar 

  96. Petoussi-Henss, N., Zankl, M., Fill, U., Regulla, D.: The GSF family of voxel phantoms. Phys. Med. Biol. 47, 89–106 (2002)

    Article  Google Scholar 

  97. Fill, U.A., Zankl, M., Petoussi-Henss, N., Siebert, M., Regulla, D.: Adult female voxel models of different stature and photon conversion coefficients for radiation protection. Health Phys. 86(3), 253–272 (2004)

    Article  Google Scholar 

  98. Petoussi, N., et al.: Organ doses for fetuses, babies, children and adults from environmental gamma-rays. Radiat. Prot. Dosim. 37, 31 (1991)

    Article  Google Scholar 

  99. Veit, R., Zankl, M., Petoussi, N., Mannweiler, E., Williams, G., Drexler, G.: Tomographic anthropomorphic models, Part i: construction technique and description of models of an 8 week old baby and a 7 year old child. GSF-Report 3, 89 (1989)

    Google Scholar 

  100. Zankl, M., Panzer, W., Drexler, G.: Tomographic anthropomorphic models: part II: organ doses from computed tomographic examination in paediatric radiology. GSF-Bericht No. 30/93 (1993)

    Google Scholar 

  101. Stratis, A., Touyz, N., Zhang, G., Jacobs, R., Bogaerts, R., Bosmans, H., DIMITRA project partners.: Development of a paediatric head voxel model database for dosimetric applications. Br. J. Radiol. 90(1078), 20170051 (2017)

    Google Scholar 

  102. Shi, C., Xu, X.G.: Development of a 30-week-pregnant female tomographic model from computed tomography (CT) images for Monte Carlo organ dose calculations. Med. Phys. 31(9), 2491–2497 (2004)

    Article  Google Scholar 

  103. Loftis, K., Halsey, M., Anthony, E., Duma, S.M., Stitzel, J.: Pregnant female anthropometry from ct scans for finite element model development. Biomed. Sci. Instrum. 44, 355–360 (2008)

    Google Scholar 

  104. Kramer, R., Vieira, J.W., Khoury, H.J., Lima, F.R.A., Fuelle, D.: All about MAX: a male adult voxel phantom for Monte Carlo calculations in radiation protection dosimetry. Phys. Med. Biol. 48(10), 1239 (2003)

    Article  Google Scholar 

  105. Kramer, R., Khoury, H.J., Vieira, J.W., Loureiro, E.C.M., Lima, V.J.M., Lima, F.R.A., Hoff, G.: All about FAX: a female adult voXel phantom for Monte Carlo calculation in radiation protection dosimetry. Phys. Med. Biol. 49(23), 5203 (2004)

    Article  Google Scholar 

  106. Sato, K., Noguchi, H., Emoto, Y., Koga, S., Saito, K.: Japanese adult male voxel phantom constructed on the basis of CT images. Radiat. Prot. Dosim. 123(3), 337–344 (2006)

    Article  Google Scholar 

  107. Sato, K., Noguchi, H., Emoto Koga, Y., Saito, K.: Construction of a Japanese adult female voxel phantom for internal dosimetry. Radiat. Environ. Biophys. (2007)

    Google Scholar 

  108. van der Heyden, B., Schyns, L.E., Podesta, M., Vaniqui, A., Almeida, I.P., Landry, G., Verhaegen, F.: VOXSI: a voxelized single-and dual-energy CT scenario generator for quantitative imaging. Phys. Imag. Radiat. Oncol. 6, 47–52 (2018)

    Article  Google Scholar 

  109. Winslow, M., Xu, X.G., Yazici, B.: Development of a simulator for radiographic image optimization. Comput. Methods Programs Biomed. 78(3), 179–190 (2005)

    Article  Google Scholar 

  110. Son, I.Y., Winslow, M., Yazici, B., Xu, X.G.: X-ray imaging optimization using virtual phantoms and computerized observer modelling. Phys. Med. Biol. 51(17), 4289 (2006)

    Article  Google Scholar 

  111. Larsson, E., Strand, S.E., Ljungberg, M., Jönsson, B.A.: Mouse S-factors based on Monte Carlo simulations in the anatomical realistic Moby phantom for internal dosimetry. Cancer Biother. Radiopharm. 22(3), 438–442 (2007)

    Article  Google Scholar 

  112. Kostou, T., Papadimitroulas, P., Loudos, G., Kagadis, G.C.: A preclinical simulated dataset of S-values and investigation of the impact of rescaled organ masses using the MOBY phantom. Phys. Med. Biol. 61(6), 2333 (2016)

    Article  Google Scholar 

  113. Dimbylow, P.J.: FDTD calculations of the whole-body averaged SAR in an anatomically realistic voxel model of the human body from 1 MHz to 1 GHz. Phys. Med. Biol. 42, 479 (1997)

    Article  Google Scholar 

  114. Dimbylow, P.: Development of the female voxel phantom, NAOMI, and its application to calculations of induced current densities and electric fields from applied low frequency magnetic and electric fields. Phys. Med. Biol. 50, 1047 (2005)

    Article  Google Scholar 

  115. Dimbylow, P., Bolch, W.: Whole-body-averaged SAR from 50 MHz to 4 GHz in the University of Florida child voxel phantoms. Phys. Med. Biol. 52(22), 6639 (2007)

    Article  Google Scholar 

  116. Ferrari, P., Gualdrini, G.: An improved MCNP version of the NORMAN voxel phantom for dosimetry studies. Phys. Med. Biol. 50(18), 4299 (2005)

    Article  Google Scholar 

  117. Nagaoka, T., Watanabe, S., Sakurai, K., Kuneida, E., Watanabe, S., Taki, M., Yamanka, Y.: Development of realistic high resolution whole-body voxel models of Japanese adult male and female of average height and weight, and application of models to radio-frequency electromagnetic-field dosimetry. Phys. Med. Biol. 49, 1–15 (2004)

    Article  Google Scholar 

  118. Lee, C., Nagaoka, T., Lee, J.K.: Implementation of Japanese male and female tomographic phantoms to multi-particle Monte Carlo code for ionizing radiation dosimetry. J. Nucl. Sci. Technol. 43, 937 (2006)

    Article  Google Scholar 

  119. Nagaoka, T., et al.: An anatomically realistic whole-body pregnant-woman model and specific absorption rates for pregnant-woman exposure to electromagnetic plane waves from 10 MHz to 2 GHz. Phys. Med. Biol. 52, 6731 (2007)

    Article  Google Scholar 

  120. Lee, C., Lee, J., Lee, C.: Korean adult male voxel model KORMAN segmented from magnetic resonance images. Med. Phys. 31, 1017 (2004)

    Article  Google Scholar 

  121. Park, S.H., et al.: In vivo organ mass of Korean adults obtained from whole-body magnetic resonance data. Radiat. Prot. Dosim. 118, 275 (2006)

    Article  Google Scholar 

  122. Li, J.L., et al.: Organ dose conversion coefficients for external photon irradiation using the Chinese voxel phantom (CVP). Radiat. Prot. Dosim. (2009)

    Google Scholar 

  123. Becker, J., Zankl, M., Fill, U., Hoeschen, C.: Katja—the 24th week of virtual pregnancy for dosimetric calculations. Pol. J. Med. Phys. Eng. 14(1), 13–20 (2008)

    Google Scholar 

  124. Gosselin, M.C., Neufeld, E., Moser, H., Huber, E., Farcito, S., Gerber, L., Jedensjö, M., Hilber, I., Di Gennaro, F., Lloyd, B., Cherubini, E.: Development of a new generation of high-resolution anatomical models for medical device evaluation: the virtual population 3.0. Phys. Med. Biol. 59(18), 5287 (2014)

    Article  Google Scholar 

  125. Rispoli, J.V., Wright, S.M., Malloy, C.R., McDougall, M.P.: Automated modification and fusion of voxel models to construct body phantoms with heterogeneous breast tissue: application to MRI simulations. J. Biomed. Graph. Comput. 7(1), 1 (2017)

    Article  Google Scholar 

  126. Lucano, E., Liberti, M., Lloyd, T., Apollonio, F., Wedan, S., Kainz, W., Angelone, L.M.: A numerical investigation on the effect of RF coil feed variability on global and local electromagnetic field exposure in human body models at 64 MHz. Magn. Reson. Med. 79(2), 1135–1144 (2018)

    Article  Google Scholar 

  127. Li, C., Chen, Z., Yang, L., Lv, B., Liu, J., Varsier, N., Hadjem, A., Wiart, J., Xie, Y., Ma, L., Wu, T.: Generation of infant anatomical models for evaluating electromagnetic field exposures. Bioelectromagnetics 36(1), 10–26 (2015)

    Article  Google Scholar 

  128. Sakellios, N., Rubio, J.L., Karakatsanis, N., Kontaxakis, G., Loudos, G., Santos, A., Nikita, K., Majewski, S.: GATE simulations for small animal SPECT/PET using voxelized phantoms and rotating-head detectors. In: 2006 IEEE Nuclear Science Symposium Conference Record, vol. 4, pp. 2000–2003. IEEE (2006, October)

    Google Scholar 

  129. Jackson, P.A., Beauregard, J.M., Hofman, M.S., Kron, T., Hogg, A., Hicks, R.J.: An automated voxelized dosimetry tool for radionuclide therapy based on serial quantitative SPECT/CT imaging. Med. Phys. 40(11), 112503 (2013)

    Article  Google Scholar 

  130. Cech, R., Leitgeb, N., Pediaditis, M.: Fetal exposure to low frequency electric and magnetic fields. Phys. Med. Biol. 52(4), 879 (2007)

    Article  Google Scholar 

  131. Xu, X.G., Taranenko, V., Zhang, J., Shi, C.: A boundary-representation method for designing whole-body radiation dosimetry models: pregnant females at the ends of three gestational periods—RPI-P3,-P6 and-P9. Phys. Med. Biol. 52(23), 7023 (2007)

    Article  Google Scholar 

  132. Sachse, F.B., Werner, C., Müller, M., Meyer-Waarden, K.: MEET Man-Models for Simulation of Electromagnetic, Elastomechanic and Thermic Behavior of Man. Erstellung und technische Parameter. Institut für Biomedizinische Technik, Technische Universität Karlsruhe, Karlsruhe (1997)

    Google Scholar 

  133. Bibin, L., Anquez, J., Angelini, E., Bloch, I.: Hybrid 3D pregnant woman and fetus modeling from medical imaging for dosimetry studies. Int. J. Comput. Assist. Radiol. Surg. 5(1), 49 (2010)

    Article  Google Scholar 

  134. Hurtado, J.L., Lee, C., Lodwick, D., Goede, T., Williams, J.L., Bolch, W.E.: Hybrid computational phantoms representing the reference adult male and adult female: construction and applications for retrospective dosimetry. Health Phys. 102(3) (2012)

    Article  Google Scholar 

  135. Rauwendaal, R.: Hybrid computational voxelization using the graphics pipeline (2012)

    Google Scholar 

  136. Janßen, C.F., Koliha, N., Rung, T.: A fast and rigorously parallel surface voxelization technique for GPU-accelerated CFD simulations. Commun. Comput. Phys. 17(5), 1246–1270 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  137. Nyirenda, P.J., Bronsvoort, W.F.: Numeric and curve parameters for freeform surface feature models. Comput.-Aided Des. 40(8), 839–851 (2008)

    Article  Google Scholar 

  138. Kobbelt, L.P., Bischoff, S., Botsch, M., Kähler, K., Rössl, C., Schneider, R., Vorsatz, J.: Geometric Modeling Based on Polygonal Meshes, vol. 1. Max-Planck-Institut für Informatik (2000)

    Google Scholar 

  139. Segars, W.P.: Development and application of the new dynamic Nurbs-based Cardiac-Torso (NCAT) phantom (2002)

    Google Scholar 

  140. Segars, W.P., Tsui, B.M.: Study of the efficacy of respiratory gating in myocardial SPECT using the new 4-D NCAT phantom. IEEE Trans. Nucl. Sci. 49(3), 675–679 (2002)

    Article  Google Scholar 

  141. Veress, A.I., Segars, W.P., Weiss, J.A., Tsui, B.M., Gullberg, G.T.: Normal and pathological NCAT image and phantom data based on physiologically realistic left ventricle finite-element models. IEEE Trans. Med. Imag. 25(12), 1604–1616 (2006)

    Article  Google Scholar 

  142. Segars, W.P., Taguchi, K., Fung, G.S.K., Fishman, E.K., Tsui, B.M.W.: Effect of heart rate on CT angiography using the enhanced cardiac model of the 4D NCAT. In: Medical Imaging 2006: Physics of Medical Imaging, vol. 6142, p. 61420I. International Society for Optics and Photonics (2006, March)

    Google Scholar 

  143. Garrity, J.M., Segars, W.P., Knisley, S.B., Tsui, B.M.: Development of a dynamic model for the lung lobes and airway tree in the NCAT phantom. IEEE Trans. Nucl. Sci. 50(3), 378–383 (2003)

    Article  Google Scholar 

  144. Segars, W.P., Mori, S., Chen, G.T.Y., Tsui, B.M.W.: Modeling respiratory motion variations in the 4D NCAT phantom. In: 2007 IEEE Nuclear Science Symposium Conference Record, vol. 4, pp. 2677–2679. IEEE (2007, October)

    Google Scholar 

  145. McGurk, R., Seco, J., Riboldi, M., Wolfgang, J., Segars, P., Paganetti, H.: Extension of the NCAT phantom for the investigation of intra-fraction respiratory motion in IMRT using 4D Monte Carlo. Phys. Med. Biol. 55(5), 1475 (2010)

    Article  Google Scholar 

  146. Zhang, J., Xu, X. G., Shi, C., Fuss, M.: Development of a geometry‐based respiratory motion–simulating patient model for radiation treatment dosimetry. J. Appl. Clin. Med. Phys. 9(1), 16–28 (2008)

    Article  Google Scholar 

  147. Segars, W.P., Tsui, B.M., Frey, E.C., Fishman, E.K.: Extension of the 4D NCAT phantom to dynamic x-ray CT simulation. In: 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No. 03CH37515), vol. 5, pp. 3195–3199. IEEE (2003, October)

    Google Scholar 

  148. Segars, W.P., Mahesh, M., Beck, T., Frey, E.C., Tsui, B.M.W.: Validation of the 4D NCAT simulation tools for use in high-resolution x-ray CT research. In: Medical Imaging 2005: Physics of Medical Imaging, vol. 5745, pp. 828–835. International Society for Optics and Photonics (2005, April)

    Google Scholar 

  149. Segars, W.P., Tsui, B.M., Da Silva, A.J., Shao, L.: CT-PET image fusion using the 4D NCAT phantom with the purpose of attenuation correction. In: 2002 IEEE Nuclear Science Symposium Conference Record, vol. 3, pp. 1775–1779. IEEE (2002, November)

    Google Scholar 

  150. Segars, W.P., Tsui, B.M.: MCAT to XCAT: The evolution of 4-D computerized phantoms for imaging research. Proc. IEEE 97(12), 1954–1968 (2009)

    Article  Google Scholar 

  151. Segars, W.P., Bond, J., Frush, J., Hon, S., Eckersley, C., Williams, C.H., Feng, J., Frush, D., Tward, D.J., Ratnanather, J.T., Miller, M.I., Frush, D.: Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization. Med. Phys. 40(4), 043701 (2013)

    Article  Google Scholar 

  152. Norris, H., Zhang, Y., Bond, J., Sturgeon, G.M., Minhas, A., Tward, D.J., Ratnanather, J.T., Miller, M.I., Frush, D., Samei, E., Segars, W.P.: A set of 4D pediatric XCAT reference phantoms for multimodality research. Med. Phys. 41(3) (2014)

    Article  Google Scholar 

  153. Geyer, A.M., O’Reilly, S., Lee, C., Long, D.J., Bolch, W.E.: The UF/NCI family of hybrid computational phantoms representing the current US population of male and female children, adolescents, and adults—application to CT dosimetry. Phys. Med. Biol. 59(18), 5225 (2014)

    Article  Google Scholar 

  154. Segars, W., Tsui, B.: 4D MOBY and NCAT phantoms for medical imaging simulation of mice and men. J. Nucl. Med. 48(Supplement 2), 203P–203P (2007)

    Google Scholar 

  155. Keenan, M.A., Stabin, M.G., Segars, W.P., Fernald, M.J.: RADAR realistic animal model series for dose assessment. J. Nucl. Med. 51(3), 471–476 (2010)

    Article  Google Scholar 

  156. Stabin, M., Xu, X., Emmons, M., Segars, W., Shi, C., Fernald, M.: RADAR reference adult, pediatric, and pregnant female phantom series for internal and external dosimetry. J. Nucl. Med. 53(11), 1807–1813 (2012)

    Article  Google Scholar 

  157. Kostou, T., Papadimitroulas, P., Loudos, G., Kagadis, G.C.: A preclinical simulated dataset of S-values and investigation of the impact of rescaled organ masses using the MOBY phantom. Phys. Med. Biol. 61(6), 2333 (2016)

    Article  Google Scholar 

  158. Dogdas, B., Stout, D., Chatziioannou, A.F., Leahy, R.M.: Digimouse: a 3D whole body mouse atlas from CT and cryosection data. Phys. Med. Biol. 52(3), 577 (2007)

    Article  Google Scholar 

  159. Xie, T., Zaidi, H.: Development of computational small animal models and their applications in preclinical imaging and therapy research. Med. Phys. 43(1), 111–131 (2016)

    Article  Google Scholar 

  160. Zhang, J., Na, Y., Caracappa, P., Xu, X.: RPI-AM and RPI-AF, a pair of mesh-based, size-adjustable adult male and female computational phantoms using ICRP-89 parameters and their calculations for organ doses from monoenergetic photon beams. Phys. Med. Biol. 54(19), 5885–5908 (2009)

    Article  Google Scholar 

  161. Cassola, V.F., de Melo Lima, V.J., Kramer, R., Khoury, H.J.: FASH and MASH: female and male adult human phantoms based on polygon mesh surfaces: I. Development of the anatomy. Phys. Med. Biol 55(1), 133 (2009)

    Article  Google Scholar 

  162. Kramer, R., Cassola, V.F., Khoury, H.J., Vieira, J.W., de Melo Lima, V.J., Brown, K.R.: FASH and MASH: female and male adult human phantoms based on polygon mesh surfaces: II. Dosimetric calculations. Phys. Med. Biol. 55(1), 163 (2009)

    Article  Google Scholar 

  163. Cassola, V.F., Milian, F.M., Kramer, R., de Oliveira Lira, C.A.B., Khoury, H.J.: Standing adult human phantoms based on 10th, 50th and 90th mass and height percentiles of male and female caucasian populations. Phys. Med. Biol. 56(13), 3749 (2011)

    Article  Google Scholar 

  164. Kim, C.H., Jeong, J.H., Bolch, W.E., Cho, K.W., Hwang, S.B.: A polygon-surface reference Korean male phantom (PSRK-Man) and its direct implementation in Geant4 Monte Carlo simulation. Phys. Med. Biol. 56(10), 3137 (2011)

    Article  Google Scholar 

  165. Kim, C.H., Yeom, Y.S., Nguyen, T.T., Wang, Z.J., Kim, H.S., Han, M.C., Lee, J.K., Zankl, M., Petoussi-Henss, N., Bolch, W.E., Lee, C.: The reference phantoms: voxel vs polygon. Ann. ICRP 45(1_suppl), 188–201 (2016)

    Article  Google Scholar 

  166. Park, J.S., Jung, Y.W., Lee, J.W., Shin, D.S., Chung, M.S., Riemer, M., Handels, H.: Generating useful images for medical applications from the visible Korean human. Comput. Methods Programs Biomed. 92(3), 257–266 (2008)

    Article  Google Scholar 

  167. Ghista, D., Sandler, H.: An analytic elastic-viscoelastic model for the shape and the forces in the left ventricle. J. Biomech. 2, 35–47 (1969)

    Article  Google Scholar 

  168. van den Broek, J., van den Broek, M.: Application of an ellipsoidal heart model in studying left ventricular contractions. J. Biomech. 13(6), 493–503 (1980)

    Article  Google Scholar 

  169. Kerckhoffs, R.C.P., Bovendeerd, P.H.M., Kotte, J.C.S., Prinzen, F.W., Smits, K., Arts, T.: Homogeneity of cardiac contraction despite physiological asynchrony of depolarization: a model study. Ann. Biomed. Eng. 31, 536–547 (2003)

    Article  Google Scholar 

  170. Sermesant, M., Moireau, P., Camara, O., Sainte-Marie, J., Andriantsimiavona, R., Cimrman, R., et al.: Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties. Med. Image Anal. 10, 642–656 (2006)

    Article  Google Scholar 

  171. Tsui, B., Terry, J., Gullberg, G.: Evaluation of cardiac cone-beam single photon emission computed tomography using observer performance experiments and receiver operating characteristic analysis. Invest. Radiol. 28(12), 1101–1112 (1993)

    Article  Google Scholar 

  172. Pretorius, P.H., Xia, W., King, M.A., Tsui, B.M.: Evaluation of right and left ventricular volume and ejection fraction using a mathematical cardiac torso phantom. J. Nucl. Med. 38(10), 1528 (1997)

    Google Scholar 

  173. Gibb, M., Bishop, M., Burton, R., Kohl, P., Grau, V., Plank, G., Rodriguez, B.: The role of blood vessels in rabbit propagation dynamics and cardiac arrhythmias. In: International Conference on Functional Imaging and Modeling of the Heart, pp. 268–276. Springer, Berlin, Heidelberg (2009)

    Chapter  Google Scholar 

  174. Lee, C., Williams, J., Lee, C., Bolch, W.: The UF series of tomographic computational phantoms of pediatric patients. Med. Phys. 32(12), 3537–3548 (2005)

    Article  Google Scholar 

  175. Werner, C.D., Sachse, F.B., Dössel, O.: Electrical excitation propagation in the human heart. Int. J. Bioelectromagn. 2(2) (2000)

    Google Scholar 

  176. Deng, D., Jiao, P., Ye, X., Xia, L.: An image-based model of the whole human heart with detailed anatomical structure and fiber orientation. Comput. Math. Methods Med. 2012, 1–16 (2012)

    Article  MathSciNet  Google Scholar 

  177. Farah, J., Broggio, D., Franck, D.: Creation and use of adjustable 3d phantoms: application for the lung monitoring of female workers. Health Phys. 99(5), 649–661 (2010)

    Article  Google Scholar 

  178. Potse, M., Dube, B., Richer, J., Vinet, A., Gulrajani, R.: A comparison of monodomain and bidomain reaction-diffusion models for action potential propagation in the human heart. IEEE Trans. Biomed. Eng. 53(12), 2425–2435 (2006)

    Article  Google Scholar 

  179. Utkualp, N., Ercan, I.: Anthropometric measurements usage in medical sciences. Biomed. Res. Int. 2015, 1–7 (2015)

    Article  Google Scholar 

  180. Tanaka, G., Kawamura, H., Griffith, R., Cristy, M., Eckerman, K.: Reference man models for males and females of six age groups of Asian populations. Radiat. Prot. Dosim. 79(1), 383–386 (1998)

    Article  Google Scholar 

  181. Lee, C.S., Lee, J.K.: Computational anthropomorphic phantoms for radiation protection dosimetry: evolution and prospects. Nucl. Eng. Technol. 38(3), 239–250 (2006)

    Google Scholar 

  182. Tusscher, K.H.W.J.T., Hren, R., Panfilov, A.V.: Organization of ventricular fibrillation in the human heart. Circ. Res. 100, e87–e101 (2007)

    Google Scholar 

  183. Fleureau, J., Garreau, M., Donal, E., Leclercq, C., Hernández, A.: A hybrid tissue-level model of the left ventricle: application to the analysis of the regional cardiac function in heart failure. In: International Conference on Functional Imaging and Modeling of the Heart, pp. 258–267. Springer, Berlin, Heidelberg (2009)

    Chapter  Google Scholar 

  184. Pravdin, S.: A mathematical spline-based model of cardiac left ventricle anatomy and morphology. Computation 4(4), 42 (2016)

    Article  Google Scholar 

  185. Krishnamurthy, A., Gonzales, M., Sturgeon, G., Segars, W., McCulloch, A.: Biomechanics simulations using cubic Hermite meshes with extraordinary nodes for isogeometric cardiac modeling. Comput. Aided Geom. Des. 43, 27–38 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  186. Loewe, A., Krueger, M.W., Holmqvist, F., Dössel, O., Seemann, G., Platonov, P.G.: Influence of the earliest right atrial activation site and its proximity to interatrial connections on P-wave morphology. EP Europace, 18(suppl_4), iv35–iv43 (2016)

    Google Scholar 

  187. Chang, K., Trayanova, N.: Mechanisms of arrhythmogenesis related to calcium-driven alternans in a model of human atrial fibrillation. Sci. Rep. 6(1) (2016)

    Google Scholar 

  188. Harrild, D.M., Henriquez, C.S.: A computer model of normal conduction in the human atria. Circ. Res. 87, E25–E36 (2000)

    Google Scholar 

  189. Jacquemet, V., Virag, N., Ihara, Z., Dang, L., Blanc, O., et al.: Study of unipolar electrogram morphology in a computer model of atrial fibrillation. J. Cardiovasc. Electrophysiol. 14, S172–S179 (2003)

    Article  Google Scholar 

  190. Reumann, M., Bohnert, J., Seemann, G., Osswald, B., Dossel, O.: Preventive ablation strategies in a biophysical model of atrial fibrillation based on realistic anatomical data. IEEE Trans. Biomed. Eng. 55(2), 399–405 (2008)

    Article  Google Scholar 

  191. Plank, G., Prassl, A.J., Wang, J.I., Seemann, G., Scherr, D., et al.: Atrial fibrosis promotes the transition of pulmonary vein ectopy into reentrant arrhythmias. Heart Rhythm 5, S162–S163 (2008)

    Google Scholar 

  192. Kim, H., Vignon-Clementel, I., Coogan, J., Figueroa, C., Jansen, K., Taylor, C.: Patient-specific modeling of blood flow and pressure in human coronary arteries. Ann. Biomed. Eng. 38(10), 3195–3209 (2010)

    Article  Google Scholar 

  193. Biglino, G., Cosentino, D., Steeden, J., De Nova, L., Castelli, M., Ntsinjana, H., et al.: Using 4D cardiovascular magnetic resonance imaging to validate computational fluid dynamics: a case study. Front. Pediatr. 3 (2015)

    Google Scholar 

  194. Chen, K., Liu, J.: MRI image segmentation based on watershed algorithm and WKFCM algorithm. J. Electron. Meas. Instrum. 25(6), 516–521 (2011)

    Article  Google Scholar 

  195. Cutroneo, G., Bruschetta, D., Trimarchi, F., Cacciola, A., Cinquegrani, M., Duca, A., et al.: In vivo CT direct volume rendering: a three-dimensional anatomical description of the heart. Pol. J. Radiol. 81, 21–28 (2016)

    Article  Google Scholar 

  196. Mueller, D.C.: Direct volume illustration for cardiac applications. Doctoral dissertation, Queensland University of Technology (2008)

    Google Scholar 

Download references

Acknowledgements

The authors are grateful for funding supports by Universiti Teknologi Malaysia and Ministry of Higher Education Malaysia under FRGS Grant. J130000.7845.4F764 and GUP Tier 1 Grant Q.J130000.2545.20H36

Author information

Authors and Affiliations

  1. IJN-UTM Cardiovascular Engineering Center, Institute of Human Centered Engineering, Johor Bahru, Malaysia

    Nurulazirah Md Salih & Dyah Ekashanti Octorina Dewi

  2. School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Nurulazirah Md Salih & Dyah Ekashanti Octorina Dewi

Authors
  1. Nurulazirah Md Salih
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dyah Ekashanti Octorina Dewi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dyah Ekashanti Octorina Dewi .

Editor information

Editors and Affiliations

  1. School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia

    Dyah Ekashanti Octorina Dewi

  2. School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia

    Yuan Wen Hau

  3. School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia

    Ahmad Zahran Mohd Khudzari

  4. School of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia

    Ida Idayu Muhamad

  5. School of Biomedical Engineering and Health Sciences, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia

    Eko Supriyanto

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Salih, N.M., Dewi, D.E.O. (2020). Computational Human Models in Cardiovascular Imaging: From Design to Generations. In: Dewi, D., Hau, Y., Khudzari, A., Muhamad, I., Supriyanto, E. (eds) Cardiovascular Engineering. Series in BioEngineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-8405-8_3

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-8405-8_3

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8404-1

  • Online ISBN: 978-981-10-8405-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation