This book provides an introduction to the use of geometric partial differential equations in image processing and computer vision. This research area brings a number of new …
Introduction Imageprocessing, computervisionandcomputergraphicsareno…-search areas. Pattern recognition and arti? cial intelligence were the origins of the explorationofthespace …
A novel framework for solving variational problems and partial differential equations for scalar and vector-valued data defined on surfaces is introduced in this paper. The key idea …
S Chen, W Chen - Structural and Multidisciplinary Optimization, 2011 - Springer
Geometric uncertainty refers to the deviation of the geometric boundary from its ideal position, which may have a non-trivial impact on design performance. Since geometric …
A method for deforming curves in a given image to a desired position in a second image is introduced. The algorithm is based on deforming the first image toward the second one via a …
In this paper, we propose a new method to systematically address the issue of structural shape and topology optimization on free-form surfaces. A free-form surface, also termed …
C Corsi, G Saracino, A Sarti… - IEEE Transactions on …, 2002 - ieeexplore.ieee.org
The application of level set techniques to echocardiographic data is presented. This method allows semiautomatic segmentation of heart chambers, which regularizes the shapes and …
R Goldenberg, R Kimmel, E Rivlin… - IEEE Transactions on …, 2002 - ieeexplore.ieee.org
An automatic cortical gray matter segmentation from a three-dimensional (3-D) brain images [magnetic resonance (MR) or computed tomography] is a well known problem in medical …
A Leow, CL Yu, SJ Lee, SC Huang, H Protas… - NeuroImage, 2005 - Elsevier
This paper presents a novel approach to feature-based brain image warping, by using a hybrid implicit/explicit framework, which unifies many prior approaches in a common …