Medical & Biological Engineering & Computing

, Volume 46, Issue 11, pp 1139–1152 | Cite as

Patient-specific surgical planning and hemodynamic computational fluid dynamics optimization through free-form haptic anatomy editing tool (SURGEM)

  • Kerem PekkanEmail author
  • Brian Whited
  • Kirk Kanter
  • Shiva Sharma
  • Diane de Zelicourt
  • Kartik Sundareswaran
  • David Frakes
  • Jarek Rossignac
  • Ajit P. Yoganathan
Special Issue - Original Article


The first version of an anatomy editing/surgical planning tool (SURGEM) targeting anatomical complexity and patient-specific computational fluid dynamics (CFD) analysis is presented. Novel three-dimensional (3D) shape editing concepts and human–shape interaction technologies have been integrated to facilitate interactive surgical morphology alterations, grid generation and CFD analysis. In order to implement “manual hemodynamic optimization” at the surgery planning phase for patients with congenital heart defects, these tools are applied to design and evaluate possible modifications of patient-specific anatomies. In this context, anatomies involve complex geometric topologies and tortuous 3D blood flow pathways with multiple inlets and outlets. These tools make it possible to freely deform the lumen surface and to bend and position baffles through real-time, direct manipulation of the 3D models with both hands, thus eliminating the tedious and time-consuming phase of entering the desired geometry using traditional computer-aided design (CAD) systems. The 3D models of the modified anatomies are seamlessly exported and meshed for patient-specific CFD analysis. Free-formed anatomical modifications are quantified using an in-house skeletization based cross-sectional geometry analysis tool. Hemodynamic performance of the systematically modified anatomies is compared with the original anatomy using CFD. CFD results showed the relative importance of the various surgically created features such as pouch size, vena cave to pulmonary artery (PA) flare and PA stenosis. An interactive surgical-patch size estimator is also introduced. The combined design/analysis cycle time is used for comparing and optimizing surgical plans and improvements are tabulated. The reduced cost of patient-specific shape design and analysis process, made it possible to envision large clinical studies to assess the validity of predictive patient-specific CFD simulations. In this paper, model anatomical design studies are performed on a total of eight different complex patient specific anatomies. Using SURGEM, more than 30 new anatomical designs (or candidate configurations) are created, and the corresponding user times presented. CFD performances for eight of these candidate configurations are also presented.


Patient specific surgical planning Computational fluid dynamics Congenital heart defects Computer aided design 



Drs. Mark Fogel, William Gaynor at the Children’s Hospital of Philadelphia, Dr. Pedro del Nido, Boston Children’s Hospital, Paul Krishborn-Emory University and Dr. W. James Parks at Sibley Heart Center, Egleston Children’s Hospital/Emory University, Atlanta. We also thank Hiroumi Kitajima and undergraduate student Gopinath Jayaprakash for providing most of the reconstructions used in this study. Also Paymon Nourparvar and Vasu Yerneni assisted in the CFD simulations through Georgia Tech President’s Undergraduate Research Awards (PURA). Financial support: National Heart, Lung and Blood Institute Grant HL67622 and Seed Grant from the Graphics Visualization and Usability (GVU) Center at Georgia Tech.

Supplementary material




  1. 1.
    Barnett GH (1999) The role of image-guided technology in the surgical planning and resection of gliomas. J Neurooncol 42(3):247–258CrossRefMathSciNetGoogle Scholar
  2. 2.
    Barnett GH, Miller DW, Weisenberger J (1999) Frameless stereotaxy with scalp-applied fiducial markers for brain biopsy procedures: experience in 218 cases. J Neurosurg 91(4):569–576CrossRefGoogle Scholar
  3. 3.
    Cebral JR, Castro MA, Burgess JE, Pergolizzi RS, Sheridan MJ, Putman CM (2005) Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models. Am J Neuroradiol 26(10):2550–2559Google Scholar
  4. 4.
    Cheutet V, Catalano C, Pernot J, Falcidieno B, Giannini F, Leon J (2005) 3D sketching for aesthetic design using fully free-form deformation features. Comput Graph 29(6):916–930CrossRefGoogle Scholar
  5. 5.
    de Zelicourt DA, Pekkan K, Wills L, Kanter K, Forbess J, Sharma S, Fogel M, Yoganathan AP (2005) In vitro flow analysis of a patient-specific intraatrial total cavopulmonary connection. Ann Thorac Surg 79(6):2094–2102CrossRefGoogle Scholar
  6. 6.
    de Zelicourt DA, Pekkan K, Parks J, Kanter K, Fogel M, Yoganathan AP (2006) Flow study of an extracardiac connection with persistent left superior vena cava. J Thorac Cardiovasc Surg 131(4):785–791CrossRefGoogle Scholar
  7. 7.
    Deleval MR, Kilner P, Gewillig M, Bull C (1988) Total cavopulmonary connection—a logical alternative to atriopulmonary connection for complex Fontan operations—experimental studies and early clinical-experience. J Thoracic Cardiovasc Surg 96(5):682–695Google Scholar
  8. 8.
    Dubini G, Migliavacca F, Pennati G, de Leval MR, Bove EL (2004) Ten years of modelling to achieve haemodynamic optimisation of the total cavopulmonary connection. Cardiol Young 14(Suppl 3):48–52Google Scholar
  9. 9.
    Duncan J (1989) Computer-aided sculpture. Cambridge University Press, LondonGoogle Scholar
  10. 10.
    Ensley AE, Lynch P, Chatzimavroudis GP, Lucas C, Sharma S, Yoganathan AP (1999) Toward designing the optimal total cavopulmonary connection: an in vitro study. Ann Thorac Surg 68(4):1384–1390CrossRefGoogle Scholar
  11. 11.
    Fang X, Bao H, Pheng A, Tien T, Peng Q (2001) Continuous field based free-form surface modeling and morphing. Comput Graph 25(2):235–243CrossRefGoogle Scholar
  12. 12.
    Frakes DH, Conrad CP, Healy TM, Monaco JW, Fogel M, Sharma S, Smith MJ, Yoganathan AP (2003) Application of an adaptive control grid interpolation technique to morphological vascular reconstruction. IEEE Trans Biomed Eng 50(2):197–206CrossRefGoogle Scholar
  13. 13.
    Frakes DH, Smith MJ, Parks J, Sharma S, Fogel SM, Yoganathan AP (2005) New techniques for the reconstruction of complex vascular anatomies from MRI images. J Cardiovasc Magn Reson 7(2):425–432CrossRefGoogle Scholar
  14. 14.
    Frakes DH, Dasi LP, Pekkan K, Kitajima HD, Sundareswaran K, Yoganathan AP, Smith MJ (2008) A new method for registration-based medical image interpolation. IEEE Trans Med Imaging 27(3):370–377CrossRefGoogle Scholar
  15. 15.
    Gildenberg PL, Labuz J (2006) Use of a volumetric target for image-guided surgery. Neurosurgery 59(3):651–659 discussion 651–659CrossRefGoogle Scholar
  16. 16.
    Giordana S, Sherwin SJ, Peiro J, Doorly DJ, Crane JS, Lee KE, Cheshire NJ, Caro CG (2005) Local and global geometric influence on steady flow in distal anastomoses of peripheral bypass grafts. J Biomech Eng 127(7):1087–1098CrossRefGoogle Scholar
  17. 17.
    Gu H, Chua A, Tan B, Hung K (2006) Nonlinear finite element simulation to elucidate the efficacy of slit arteriotomy for end-to-side arterial anastomosis in microsurgery. J Biomech 39(3):435–443Google Scholar
  18. 18.
    Hui K (2003) Free-form deformation of constructive shell models. Comput Aided Des 35(13):1221–1234CrossRefMathSciNetGoogle Scholar
  19. 19.
    Hunter KS, Lanning CJ, Chen SY, Zhang Y, Garg R, Ivy DD, Shandas R (2006) Simulations of congenital septal defect closure and reactivity testing in patient-specific models of the pediatric pulmonary vasculature: a 3D numerical study with fluid-structure interaction. J Biomech Eng 128(4):564–572CrossRefGoogle Scholar
  20. 20.
    Jackson MJ, Bicknell CD, Zervas V, Cheshire NJ, Sherwin SJ, Giordana S, Peiro J, Papaharilaou Y, Doorly DJ, Caro CG (2003) Three-dimensional reconstruction of autologous vein bypass graft distal anastomoses imaged with magnetic resonance: clinical and research applications. J Vasc Surg 38(3):621–625CrossRefGoogle Scholar
  21. 21.
    Kanter K, Krishnankutty RR, Dasi L, Kitajima H, Pekkan K, Fogel M, Witehead K, Sharma S, Yoganathan A (2008) Total cavopulmonary connection efficiency: importance of pulmonary artery diameter. J Thoracic Cardiovasc Surg (in press)Google Scholar
  22. 22.
    Kasik D, Buxton W, Ferguson D (2005) Ten CAD challenges. IEEE Comput Graph Appl 25(2):84–92CrossRefGoogle Scholar
  23. 23.
    Kim J, Rossignac J (2000) Screw motions for the animation and analysis of mechanical assemblies. Int J Jpn Soc Mech Eng 44(1):156–163Google Scholar
  24. 24.
    Kim B, Rossignac J (2003) Collision prediction for polyhedra under screw motions. ACM Symp Solid Model Appl, pp 4–10Google Scholar
  25. 25.
    Komerska R, Ware C (2004) Haptic state–surface interactions. IEEE Comput Graph Appl 24(6):52–59CrossRefGoogle Scholar
  26. 26.
    Krishnankutty R, Dasi LP, Pekkan K, Sundareswaran KS, Fogel M, Sharma S, Kanter K, Yoganathan AP (2008) Quantitative analysis of extra-cardiac vs intra-atrial Fontan anatomic geometries. Ann Thoracic Surg 85(3):810–817CrossRefGoogle Scholar
  27. 27.
    Krishnankuttyrema R, Dasi L, Pekkan K, Sundareswaran K, Kitajima H, Yoganathan AP (2007) A unidimensional representation of the total cavopulmonary connection. In: ASME 2007 summer bioengineering conference (SBC2007), ASME, Keystone Resort and Conference Center, KeystoneGoogle Scholar
  28. 28.
    Kurodaa Y, Nakaob M, Kurodac T, Oyamad H, Komorie M (2005) Interaction model between elastic objects for haptic feedback considering collisions of soft tissue. Comput Methods Programs Biomed 80:216–224CrossRefGoogle Scholar
  29. 29.
    Laks H, Ardehali A, Grant PW, Permut L, Aharon A, Kuhn M, Isabel-Jones J, Galindo A (1995) Modification of the Fontan procedure. Superior vena cava to left pulmonary artery connection and inferior vena cava to right pulmonary artery connection with adjustable atrial septal defect. Circulation 91(12):2943–2947Google Scholar
  30. 30.
    Lanning C, Chen SY, Hansgen A, Chang D, Chan KC, Shandas R (2004) Dynamic three-dimensional reconstruction and modeling of cardiovascular anatomy in children with congenital heart disease using biplane angiography. Biomed Sci Instrum 40:200–205Google Scholar
  31. 31.
    Li Z, Kleinstreuer C (2005) Fluid–structure interaction effects on sac-blood pressure and wall stress in a stented aneurysm. J Biomech Eng 127(4):662–671CrossRefGoogle Scholar
  32. 32.
    Li Z, Kleinstreuer C (2006) Effects of major endoleaks on a stented abdominal aortic aneurysm. J Biomech Eng 128(1):59–68CrossRefGoogle Scholar
  33. 33.
    Lin Y, Wang C, Dai K (2005) Reverse engineering in CAD model reconstruction of customized artificial joint. Med Eng Phys 27(2):189–193CrossRefGoogle Scholar
  34. 34.
    Linte C, Wierzbicki M, Moore J, Guiraudon G, Jones D, Peters T (2007) On enhancing planning and navigation of beating-heart mitral valve surgery using pre-operative cardiac models. In: 29th IEEE EMBS annual international conference, LyonGoogle Scholar
  35. 35.
    Llamas I, Kim B, Gargus J, Rossignac J, Shaw C (2003) Twister: a space-warp operator for the two-handed editing of 3D shapes. In: Proceeding ACM SIGGRAPH, p 663Google Scholar
  36. 36.
    Llamas I, Powell A, Rossignac J, Shaw CD (2005) Bender: a virtual ribbon for deforming 3D shapes in biomedical and styling applications. In: ACM symposium on solid modeling and applications, pp 89–99Google Scholar
  37. 37.
    Mackerle J (2004) Finite element modelling and simulations in dentistry: a bibliography 1990–2003. Comput Methods Biomech Biomed Eng 7(5):277–303CrossRefGoogle Scholar
  38. 38.
    Mario R (2006) Polygonal modeling: basic and advanced techniques. Wordware Pub, PlanoGoogle Scholar
  39. 39.
    Migliavacca F, de Leval MR, Dubini G, Pietrabissa R, Fumero R (1999) Computational fluid dynamic simulations of cavopulmonary connections with an extra-cardiac lateral conduit. Med Eng Phys 21:187–193CrossRefGoogle Scholar
  40. 40.
    Migliavacca F, Kilner PJ, Pennati G, Dubini G, Pietrabissa R, Fumero R, de Leval MR (1999) Computational fluid dynamic and magnetic resonance analyses of flow distribution between the lungs after total cavopulmonary connection. IEEE Trans Biomed Eng 46(4):393–399CrossRefGoogle Scholar
  41. 41.
    Migliavacca F, Dubini G, Bove E, de Leval M (2003) Computational fluid dynamics simulations in realistic 3-D geometries of the total cavopulmonary anastomosis: the influence of the inferior caval anastomosis. J Biomech Eng 125(6):805–813CrossRefGoogle Scholar
  42. 42.
    Mitchell ME, Ittenbach RF, Gaynor JW, Wernovsky G, Nicolson S, Spray TL (2006) Intermediate outcomes after the Fontan procedure in the current era. J Thoracic Cardiovasc Surg 131(1):172–180CrossRefGoogle Scholar
  43. 43.
    Moyle K, Antiga L, Steinman D (2006) Inlet conditions for image-based CFD models of the carotid bifurcation: is it reasonable to assume fully developed flow? J Biomech Eng 128(3):371–379CrossRefGoogle Scholar
  44. 44.
    Murakami H, Yoshimura N, Kitahara J, Otaka S, Ichida F, Misaki T (2006) Collision of the caval flows caused early failure of the Fontan circulation. J Thorac Cardiovasc Surg 132(5):1235–1236CrossRefGoogle Scholar
  45. 45.
    Pekkan K, ZD, Sorensen D, Kitajima H, Yoganathan AP (2005) Surgical planning of the total cavopulmonary connection using MRI, computational and experimental fluid mechanics. In: 3rd European medical and biological engineering conference, EMBEC Prague, Czech RepublicGoogle Scholar
  46. 46.
    Pekkan K, Frakes D, De Zelicourt D, Lucas CW, Parks WJ, Yoganathan AP (2005) Coupling pediatric ventricle assist devices to the Fontan circulation: simulations with a lumped-parameter model. Asaio J 51(5):618–628CrossRefGoogle Scholar
  47. 47.
    Pekkan K, Kitajima HD, de Zelicourt D, Forbess JM, Parks WJ, Fogel MA, Sharma S, Kanter KR, Frakes D, Yoganathan AP (2005) Total cavopulmonary connection flow with functional left pulmonary artery stenosis—angioplasty and fenestration in vitro. Circulation 112(21):3264–3271CrossRefGoogle Scholar
  48. 48.
    Pekkan K, Dur O, Kanter K, Sundareswaran K, Fogel M, Yoganathan A, Ündar A (2008) Neonatal aortic arch hemodynamics and perfusion during cardiopulmonary bypass. J Biomech Eng (in press)Google Scholar
  49. 49.
    Pekkan K, Krishnankutty R, Dasi L, Yerneni S, de Zélicourt D, Fogel M, Kanter K, Yoganathan A (2008) Hemodynamic performance of stage-2 univentricular reconstruction: Glenn vs. hemi-Fontan templates. Ann Biomed Eng (2nd review)Google Scholar
  50. 50.
    Pekkan K, Dasi LP, Nourparvar P, Yerneni S, Tobita K, Fogel MA, Keller B, Yoganathan A (2008) In vitro hemodynamic investigation of the embryonic aortic arch at late gestation. J Biomech 41(8):1697–1706CrossRefGoogle Scholar
  51. 51.
    Perktold K, Hofer M, Rappitsch G, Loew M, Kuban BD, Friedman MH (1998) Validated computation of physiologic flow in a realistic coronary artery branch. J Biomech 31(3):217–228CrossRefGoogle Scholar
  52. 52.
    Prosi M, Perktold K, Ding Z, Friedman MH (2004) Influence of curvature dynamics on pulsatile coronary artery flow in a realistic bifurcation model. J Biomech 37(11):1767–1775CrossRefGoogle Scholar
  53. 53.
    Qin S, Wright D, Kang J, Prieto P (2005) Incorporating 3D body motions into large-sized freeform surface conceptual design. Biomed Sci Instrum 41:271–276Google Scholar
  54. 54.
    Raghavan ML, Kratzberg J, Castro de Tolosa EM, Hanaoka MM, Walker P, da Silva ES (2005) Regional distribution of wall thickness and failure properties of human abdominal aortic aneurysm. J Biomech 39(16):3010–3016CrossRefGoogle Scholar
  55. 55.
    Rhoten RL, Luciano MG, Barnett GH (1997) Computer-assisted endoscopy for neurosurgical procedures: technical note. Neurosurgery 40(3):632–637 discussion 638CrossRefGoogle Scholar
  56. 56.
    Rossignac J, Requicha A (1987) Piecewise-circular curves for geometric modeling. IBM J Res Dev 13:296–313MathSciNetCrossRefGoogle Scholar
  57. 57.
    Saeed D, Ootaki Y, Noecker A, Weber S, Smith WA, Duncan BW, Fukamachi K (2008) The Cleveland clinic pedipump: virtual fitting studies in children using three-dimensional reconstructions of cardiac computed tomography scans. Asaio J 54(1):133–137Google Scholar
  58. 58.
    Sartipy U, Albage A, Lindblom D (2005) The Dor procedure for left ventricular reconstruction. Ten-year clinical experience. Eur J Cardio-thoracic Surg 27:1005–1010CrossRefGoogle Scholar
  59. 59.
    Sheppard L (2005) Virtual surgery brings back smiles. IEEE Comput Graph Appl 25(1):6–11CrossRefGoogle Scholar
  60. 60.
    Soerensen DD, Pekkan K, Sundareswaran KS, Yoganathan AP (2004) New power loss optimized Fontan connection evaluated by calculation of power loss using high resolution PC-MRI and CFD. Conf Proc IEEE Eng Med Biol Soc 2:1144–1147Google Scholar
  61. 61.
    Sorensen TS, Greil GF, Hansen OK, Mosegaard J (2006) Surgical simulation—a new tool to evaluate surgical incisions in congenital heart disease? Interact Cardiovasc Thorac Surg 5(5):536–539CrossRefGoogle Scholar
  62. 62.
    Steele BN, Draney MT, Ku JP, Taylor CA (2003) Internet-based system for simulation-based medical planning for cardiovascular disease. IEEE Trans Inf Technol Biomed 7(2):123–129CrossRefGoogle Scholar
  63. 63.
    Steele BN, Wan J, Ku JP, Hughes TJ, Taylor CA (2003) In vivo validation of a one-dimensional finite-element method for predicting blood flow in cardiovascular bypass grafts. IEEE Trans Biomed Eng 50(6):649–656CrossRefGoogle Scholar
  64. 64.
    Steinman DA (2002) Image-based computational fluid dynamics modeling in realistic arterial geometries. Ann Biomed Eng 30(4):483–497CrossRefGoogle Scholar
  65. 65.
    Steinman DA (2004) Image-based computational fluid dynamics: a new paradigm for monitoring hemodynamics and atherosclerosis. Curr Drug Targets Cardiovasc Haematol Disord 4(2):183–197CrossRefGoogle Scholar
  66. 66.
    Steinman DA, Taylor CA (2005) Flow imaging and computing: large artery hemodynamics. Ann Biomed Eng 33(12):1704–1709CrossRefGoogle Scholar
  67. 67.
    Steinman DA, Vorp DA, Ethier CR (2003) Computational modeling of arterial biomechanics: insights into pathogenesis and treatment of vascular disease. J Vasc Surg 37(5):1118–1128CrossRefGoogle Scholar
  68. 68.
    Sundareswaran KS, KH, Pekkan K, Soerensen DD, Yerneni V, Parks WJ, Sallee D, Yoganathan AP (2005) Flow field comparison in reverse engineered total cavopulmonary connection anatomic models: high resolution PC MRI vs CFD. In: International society of magnetic resonance in medicine (ISMRM) 13th scientific meeting, MiamiGoogle Scholar
  69. 69.
    Sundareswaran KS, Kanter KR, Kitajima HD, Krishnankutty R, Sabatier JF, Parks WJ, Sharma S, Yoganathan AP, Fogel M (2006) Impaired power output and cardiac index with hypoplastic left heart syndrome: a magnetic resonance imaging study. Ann Thoracic Surg 82(4):1267–1277CrossRefGoogle Scholar
  70. 70.
    Sundareswaran KS, Pekkan K, Dasi LP, Kitajima HD, Whitehead K, Fogel MA, Yoganathan AP (2007) Significant impact of the total cavopulmonary connection resistance on cardiac output and exercise performance in single ventricles. Circulation 116(16_MeetingAbstracts), p 479Google Scholar
  71. 71.
    Sundareswaran KS, Pekkan K, Dasi LP, Whitehead K, Sharma S, Kanter K, Fogel MA, Yoganathan AP (2008) The total cavopulmonary connection resistance: a significant impact on single ventricle hemodynamics at rest and exercise. Am J Physiol (in press)Google Scholar
  72. 72.
    Testi D, Quadrani P, Petrone M, Zannoni C, Fontana F, Viceconti M (2004) JIDE: a new software for computer-aided design of hip prosthesis. Comput Methods Programs Biomed 75:213–220CrossRefGoogle Scholar
  73. 73.
    van Dijk C, Mayer A (1997) Sketch input for conceptual surface design. Comput Ind 34(1):125–137CrossRefGoogle Scholar
  74. 74.
    Vannier MW, Marsh JL (1996) Three-dimensional imaging, surgical planning, and image-guided therapy. Radiol Clin North Am 34(3):545–563Google Scholar
  75. 75.
    Varady T, Martin R, Cox J (1997) Reverse engineering of geometric models—an introduction. Comput Aided Des 29(4):255–268CrossRefGoogle Scholar
  76. 76.
    Wang C, Pekkan K, de Zelicourt D, Horner M, Parihar A, Kulkarni A, Yoganathan AP (2007) Progress in the CFD modeling of flow instabilities in anatomical total cavopulmonary connections. Ann Biomed Eng 35(11):1840–1856CrossRefGoogle Scholar
  77. 77.
    Whitehead KK, Pekkan K, Kitajima HD, Paridon SM, Yoganathan AP, Fogel MA (2007) Nonlinear power loss during exercise in single-ventricle patients after the Fontan: insights from computational fluid dynamics. Circulation 116(11 Suppl):I165–I171Google Scholar
  78. 78.
    Yacoub M, Cohn L (2004) Novel approaches to cardiac valve repair: from structure to function: part I. Circulation 109(8):942–950CrossRefGoogle Scholar
  79. 79.
    Zélicourt D, Pekkan K, Parks WJ, Kanter K, Fogel M, Yoganathan AP (2006) Flow study of an extra-cardiac connection with persistent left superior vena cava. J Thoracic Cardiovasc Surg 131(4):785–791CrossRefGoogle Scholar
  80. 80.
    Zeng D, Ding Z, Friedman MH, Ethier CR (2003) Effects of cardiac motion on right coronary artery hemodynamics. Ann Biomed Eng 31(4):420–429CrossRefGoogle Scholar
  81. 81.
    2008 Geomagics Studio. Geomagics Durham, NC, USAGoogle Scholar
  82. 82.
    2008 Autodesk Maya. Autodesk, San Rafael, CA, USAGoogle Scholar
  83. 83.
  84. 84.
  85. 85.
  86. 86.
    2008 2nd Virtual Intracranial Stenting Challenge (VISC08).

Copyright information

© International Federation for Medical and Biological Engineering 2008

Authors and Affiliations

  • Kerem Pekkan
    • 1
    Email author
  • Brian Whited
    • 2
  • Kirk Kanter
    • 3
  • Shiva Sharma
    • 4
  • Diane de Zelicourt
    • 5
  • Kartik Sundareswaran
    • 5
  • David Frakes
    • 6
  • Jarek Rossignac
    • 2
  • Ajit P. Yoganathan
    • 5
  1. 1.Biomedical EngineeringCarnegie Mellon UniversityPittsburghUSA
  2. 2.College of ComputingGeorgia Institute of TechnologyAtlantaUSA
  3. 3.Department of Cardiothoracic SurgeryEmory University School of MedicineAtlantaUSA
  4. 4.Pediatric Cardiology AssociatesAtlantaUSA
  5. 5.Wallace H. Coulter Department of Biomedical EngineeringGeorgia Institute of Technology and Emory University School of MedicineAtlantaUSA
  6. 6.Harrington Department of Bioengineering and Electrical EngineeringArizona State UniversityTempeUSA

Personalised recommendations