Publications

  1. Sankaran, S., Yang, D. and Lim, S.-N., Multimodal Fusion Refiner Networks, arXiv preprint, 2104.03435, 2021.[manuscript]
  2. Sankaran, S., Lesage, D., Tombropoulos, R., Xiao, N., Kim, H.J., Spain, D., Schaap, M. and Taylor, C.A., Physics driven real-time blood flow simulations, Computer Methods in Applied Mechanics and Engineering, 364, 112963, 2020.[manuscript]
  3. Sankaran, S. et al., Physics driven reduced order model for real time blood flow simulations, arxiv preprint, 2019. [preprint]
  4. Modi, B.N., Sankaran, S., et al., Predicting the Physiological Effect of Revascularization in Serially Diseased Coronary Arteries: Clinical Validation of a Novel CT Coronary Angiography Based Technique, Circulation: Cardiovascular Interventions, 12/2, 2019. [preprint]
  5. Nakanishi, R., Sankaran, S.* et al., Automated Estimation of Image Quality for Coronary Computed Tomographic Angiography using Machine Learning, European Radiology, Vol.28/9, pp. 4018-4026, 2018 (* indicates equal contribution). [preprint]
  6. Sankaran, S., Kim, H-J., Choi, G. and Taylor, C., Uncertainty quantification in coronary flow simulations: impact of geometry, boundary conditions and blood viscosity, Journal of Biomechanics, 49 (12), pp. 2540–2547, 2016. [preprint]
  7. Sankaran, S., et al., HALE: Healthy area of lumen estimation for vessel stenosis quantification, Lecture notes in Computer Science: MICCAI, Vol. 9902, pp. 380-387, 2016. [preprint]
  8. Rajasethupathy, P.*, Sankaran, S.*, Marshel, J.H.*, Kim, C.K., Ferenczi, E., Lee, S.Y., Berndt, A., Ramakrishnan, C., Jaffe, A., Lo, M., Liston, C. and Deisseroth, K., Projections from neocortex mediate top-down control of memory retrieval,Nature 526, pp. 653-659, 2015. (* indicates equal contribution) [preprint]
  9. Sankaran, S., Grady, L., and Taylor, C., Fast computation of hemodynamic sensitivity to lumen segmentation uncertainty, IEEE Transactions on Medical Imaging, 34 (12), pp. 2562-2571, 2015.[preprint]
  10. Tomer, R., Lovett-Barron, M., Kauvar, I., Andalman ,A., Burns, V.M., Sankaran, S., Grosenick, L., Broxton, M., Yang, S., and Deisseroth, K. SPED light sheet microscopy: fast mapping of biological system structure and function, Cell, 163(1), pp. 1796-1806, 2015.
  11. Sankaran, S., Grady, L., and Taylor, C., Impact of geometric uncertainty on hemodynamic simulations using machine learning, Computer Methods in Applied Mechanics and Engineering, 297(1), pp. 167-190, 2015.[preprint]
  12. Ramachandra, A. B., Sankaran, S., Humphrey, J. D., and Marsden, A. L., Computational simulation of the adaptive capacity of vein grafts in response to increased pressure, Journal of biomechanical engineering, 137(3), 031009, 2015.
  13. Choi, G., Lee, J.M., Kim, H-J., Park, J-B., Sankaran, S., et al., Coronary artery axial plaque stress and its relationship with lesion geometry, JACC: Cardiovascular Imaging, 8 (10), pp. 1156-1166, 2015.
  14. Sankaran, S., Grady, L. J., and Taylor, C. A, Real-Time Sensitivity Analysis of Blood Flow Simulations to Lumen Segmentation Uncertainty, Medical Image Computing and Computer-Assisted Intervention, 1, pp. 1-8, 2014.
  15. Choi, G., Kim, H. J., Park, J. B., Lee, J. M., Sankaran, S., et al, Characterization of Lesion Shape and Hemodynamic Forces Acting on Coronary Artery Atherosclerotic Plaques using Computational Flow Dynamics and Computed Tomography Data, Journal of the American College of Cardiology, 64, 11_S, 2014.
  16. Sankaran, S., Humphrey, J. D., and Marsden, A. L., An efficient framework for optimization and parameter sensitivity analysis in arterial growth and remodeling computations, Computer methods in applied mechanics and engineering, 256, pp. 200-210, 2013.
  17. Sankaran, S., Moghadam, M.E., Kahn, A.M., Tseng, E.E., Guccione, G.M., and Marsden, A.L., Patient-specific multiscale modeling of blood flow for coronary artery bypass graft surgery, Annals of Biomedical Engineering, 40(10) pp. 2228-2242, 2012.
  18. Sengupta, D., Kahn, A. M., Burns, J. C., Sankaran, S., Shadden, S. C., and Marsden, A. L., Image-based modeling of hemodynamics in coronary artery aneurysms caused by Kawasaki disease, Biomechanics and modeling in mechanobiology, 11(6), pp. 915-932, 2012.
  19. Schriefl, A.J., Reinisch, A.J., Sankaran, S., Pierce, D.M., and Holzapfel, G.A., Quantitative assessment of collagen fibre orientations from two-dimensional images of soft biological tissues, Journal of The Royal Society Interface, 9(76), pp.3081-3093, 2012.
  20. Sankaran, S. and Marsden, A.L., A stochastic collocation method for uncertainty quantification in cardiovascular simulations, Journal of Biomechanical Engineering, 133(3), 031001, 2011. [preprint]
  21. Sankaran, S. and Marsden, A.L.,The impact of uncertainty on shape optimization of idealized bypass graft models in unsteady flow, Physics of Fluids, 22, 121902, 2010.
  22. Sankaran, S., Audet C. and Marsden A. L. A method for stochastic constrained optimization using derivative-free surrogate pattern search and collocation, Journal of Computational Physics, 20(12), pp. 4664-4682, 2010. [preprint]
  23. Bazilevs, Y, Hsu, M.-C., Besnon, D.J., Sankaran, S. and Marsden, A.L.,Computational Fluid-Structure Interaction: Methods and Application to a Total Cavopulmonary Connection, Computational Mechanics, 45(1) pp. 77-89, 2009.
  24. Sankaran, S., Stochastic optimization using a sparse-grid collocation scheme, Probabilistic Engineering Mechanics, 24(3), 382-396, 2009. [preprint]
  25. Zabaras, N., and Sankaran, S., An information-theoretic approach to stochastic materials modeling, IEEE Computing in Science and Engineering, pp. 50-59, (2007).
  26. Sankaran, S., and Zabaras, N., Computing property variability of polycrystals induced by grain size and orientation uncertainties, Acta Materialia, 55, 2279-2290, (2007).
  27. Sankaran, S., and Zabaras, N.,A maximum entropy approach for property prediction of random microstructures, Acta Materialia, 54, pp. 2265-2276, (2006).
  28. Zabaras, N., Sundararaghavan, V., and Sankaran, S., An information-theoretic approach for obtaining property PDFs from macro specifications of microstructural variability, TMS Letters, 3(1), 1-2, (2006).
  29. Balasubramaniam, K., and Sankaran, S.,Ultrasonic interferometric sensor for rheological changes of fluids, Review of Scientific Instruments, 77, 084902, (2006).