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Calibration of single-cell model parameters based on membrane resistance improves the accuracy of cardiac tissue simulations.

, , , , and . J. Comput. Sci., (2021)

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Computer Simulation of Cardiac Propagation: Effects of Fiber Rotation, Intramural Conductivity, and Optical Mapping., , , and . IEEE Trans. Biomed. Eng., 61 (7): 2041-2048 (2014)Optical Mapping System for Visualizing Arrhythmias in Isolated Mouse Atria., and . EMBC, page 4002-4005. IEEE, (2006)Improved Accuracy of Cardiac Tissue-Level Simulations by Considering Membrane Resistance as a Cellular-Level Optimization Objective., , , , and . EMBC, page 2487-2490. IEEE, (2020)Automated Masking of Voltage-Sensitive Dye Imaging Data., , and . EMBC, page 4035-4038. IEEE, (2006)Motion Estimation in Cardiac Fluorescence Imaging With Scale-Space Landmarks and Optical Flow: A Comparative Study., and . IEEE Trans. Biomed. Eng., 62 (2): 774-782 (2015)Calibration of single-cell model parameters based on membrane resistance improves the accuracy of cardiac tissue simulations., , , , and . J. Comput. Sci., (2021)Application of scale-space descriptors for the reliable detection of keypoints for image registration in optical mapping studies in whole heart preparations., and . EMBC, page 3171-3174. IEEE, (2012)Cardiac fiber rotation distorts surface measurements of anisotropic propagation., , and . EMBC, page 685-688. IEEE, (2012)Fitting Membrane Resistance in Single Cardiac Myocytes reduces Variability in Parameters., , and . CinC, page 209-212. www.cinc.org, (2014)