A High-Order Level-Set Method with Enhanced Stability for Curvature Driven Flows and Surface Diffusion Motion

2016 ◽  
Vol 69 (3) ◽  
pp. 1316-1345 ◽  
Author(s):  
Yujie Zhang ◽  
Wenjing Ye
Keyword(s):  
Surface Diffusion ◽  
Level Set Method ◽  
Level Set ◽  
High Order ◽  
Diffusion Motion ◽  
Curvature Driven ◽  
Enhanced Stability

scholarly journals Simulation of vesicle using level set method solved by high order finite element

2012 ◽  
Vol 38 ◽  
pp. 335-347 ◽  
Author(s):  
Vincent Doyeux ◽  
Vincent Chabannes ◽  
Christophe Prud’homme ◽  
Mourad Ismail
Keyword(s):  
Finite Element ◽  
Level Set Method ◽  
Level Set ◽  
High Order

Development of a high-order level set method: Compact Conservative Level Set (CCLS)

2016 ◽  
Vol 129 ◽  
pp. 79-90 ◽  
Author(s):  
Amin Mahmoudi Moghadam ◽  
Mehdi Shafieefar ◽  
Roozbeh Panahi
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
High Order ◽  
Conservative Level Set

scholarly journals Learning High-Order Geometric Flow Based on The Level Set Method

2021 ◽  
Author(s):  
Chun Li ◽  
Yunyun Yang ◽  
Hui Liang ◽  
Boying Wu
Keyword(s):  
Neural Networks ◽  
Level Set Method ◽  
Level Set ◽  
Input Data ◽  
Initial Conditions ◽  
High Order ◽  
Geometric Flow ◽  
Set Up ◽  
Almost All ◽  
Physical Phenomena

Abstract Recently, the development of deep learning (DL), which has accomplished unbelievable success in many fields, especially in scientific computational fields. And almost all computational problems and physical phenomena can be described by partial differential equations (PDEs). In this work, we proposed two potential high-order geometric flows. Motivation by the physical-information neural networks (PINNs) and the traditional level set method (LSM), we have integrated deep neural networks (DNNs) and LSM to make the proposed method more robust and efficient. Also, to test the sensitivity of the system to different input data, we set up three sets of initial conditions to test the model. Furthermore, numerical experiments on different input data are implemented to demonstrate the effectiveness and superiority of the proposed models compared to the state-of-the-art approach.

scholarly journals A High-Order Scheme for Image Segmentation via a Modified Level-Set Method

2020 ◽  
Vol 13 (1) ◽  
pp. 497-534 ◽  
Author(s):  
Maurizio Falcone ◽  
Giulio Paolucci ◽  
Silvia Tozza
Keyword(s):  
Image Segmentation ◽  
Level Set Method ◽  
Level Set ◽  
High Order ◽  
High Order Scheme ◽  
Order Scheme
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