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Liang Liang
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Year
Objective comparison of particle tracking methods
N Chenouard, I Smal, F De Chaumont, M Maška, IF Sbalzarini, Y Gong, ...
Nature methods 11 (3), 281-289, 2014
10162014
A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis
L Liang, M Liu, C Martin, W Sun
Journal of The Royal Society Interface 15 (138), 2018
3722018
A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm
L Liang, M Liu, C Martin, JA Elefteriades, W Sun
Biomechanics and Modeling in Mechanobiology 16 (5), 1519–1533, 2017
1492017
A role of OCRL in clathrin-coated pit dynamics and uncoating revealed by studies of Lowe syndrome cells
PDC Ramiro Nández, Daniel M Balkin, Mirko Messa, Liang Liang, Summer ...
elife, 2014
1232014
A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta
L Liang, W Mao, W Sun
Journal of biomechanics 99, 109544, 2020
902020
A generic physics-informed neural network-based constitutive model for soft biological tissues
M Liu, L Liang, W Sun
Computer Methods in Applied Mechanics and Engineering 372, 113402, 2020
892020
Estimation of in vivo constitutive parameters of the aortic wall using a machine learning approach
M Liu, L Liang, W Sun
Computer Methods in Applied Mechanics and Engineering, 2019
772019
Modeling Left Ventricular Blood Flow Using Smoothed Particle Hydrodynamics
A Caballero, W Mao, L Liang, J Oshinski, C Primiano, R McKay, S Kodali, ...
Cardiovascular Engineering and Technology 8 (4), 465–479, 2017
622017
Machine learning–based 3‐D geometry reconstruction and modeling of aortic valve deformation using 3‐D computed tomography images
L Liang, K Fan, C Martin, T Pham, Q Wang, JS Duncan, W Sun
International Journal of Numerical Methods in Biomedical Engineering 33 (5), 2017
622017
A Deep Learning Approach to Estimate Chemically-Treated Collagenous Tissue Nonlinear Anisotropic Stress-Strain Responses from Microscopy Images
L Liang, M Liu, W Sun
Acta Biomaterialia 63, 227-235, 2017
582017
A new inverse method for estimation of in vivo mechanical properties of the aortic wall
M Liu, L Liang, W Sun
Journal of the Mechanical Behavior of Biomedical Materials 72, 148-158, 2017
572017
Airborne particulate matter classification and concentration detection based on 3D printed virtual impactor and quartz crystal microbalance sensor
J Zhao, M Liu, L Liang, W Wang, J Xie
Sensors and Actuators A 238, 379-388, 2016
552016
A Machine Learning Approach as a Surrogate of Finite Element Analysis‐based Inverse Method to Estimate the Zero‐pressure Geometry of Human Thoracic Aorta
L Liang, M Liu, C Martin, W Sun
International journal for numerical methods in biomedical engineering 34 (8 …, 2018
382018
A novel multiple hypothesis based particle tracking method for clathrin mediated endocytosis analysis using fluorescence microscopy
L Liang, H Shen, P De Camilli, JS Duncan
IEEE Transactions on Image Processing 23 (4), 1844-1857, 2014
372014
Identification of in vivo nonlinear anisotropic mechanical properties of ascending thoracic aortic aneurysm from patient-specific CT scans
M Liu, L Liang, F Sulejmani, X Lou, G Iannucci, E Chen, B Leshnower, ...
Scientific reports 9 (1), 12983, 2019
352019
Computational optimization study of transcatheter aortic valve leaflet design using porcine and bovine leaflets
S Travaglino, K Murdock, A Tran, C Martin, L Liang, Y Wang, W Sun
Journal of biomechanical engineering 142 (1), 011007, 2020
332020
Estimation of in vivo mechanical properties of the aortic wall: A multi-resolution direct search approach
M Liu, L Liang, W Sun
Journal of the mechanical behavior of biomedical materials 77, 649-659, 2018
322018
Tracking clathrin coated pits with a multiple hypothesis based method
L Liang, H Shen, P De Camilli, J Duncan
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2010, 315-322, 2010
312010
On the computation of in vivo transmural mean stress of patient-specific aortic wall
M Liu, L Liang, H Liu, M Zhang, C Martin, W Sun
Biomechanics and Modeling in Mechanobiology, 2019
282019
Is it appropriate to measure age-related lumbar disc degeneration on the mid-sagittal MR image? A quantitative image study
X Hu, M Chen, J Pan, L Liang, Y Wang
European Spine Journal 27, 1073-1081, 2018
232018
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Articles 1–20