Fast diffeomorphic image registration via GPU-based parallel computing: an investigation of the matching cost function

2018 ◽  
Author(s):  
Jiong Wu ◽  
Xiaoying Tang
Keyword(s):  
Parallel Computing ◽  
Image Registration ◽  
Cost Function ◽  
Matching Cost ◽  
Diffeomorphic Image Registration

scholarly journals CLAIRE: Constrained Large Deformation Diffeomorphic Image Registration on Parallel Computing Architectures

2021 ◽  
Vol 6 (61) ◽  
pp. 3038
Author(s):  
Malte Brunn ◽  
Naveen Himthani ◽  
George Biros ◽  
Miriam Mehl ◽  
Andreas Mang
Keyword(s):  
Parallel Computing ◽  
Image Registration ◽  
Large Deformation ◽  
Diffeomorphic Image Registration

Diffeomorphic image registration with automatic time-step adjustment

2015 ◽  
Author(s):  
Akshay Pai ◽  
Stefan Klein ◽  
Stefan Sommer ◽  
Sune Darkner ◽  
Jon Sporring ◽  
...  
Keyword(s):  
Image Registration ◽  
Time Step ◽  
Diffeomorphic Image Registration

Computing the Medical Image Registration Using Meta-Heuristics

2014 ◽  
Vol 643 ◽  
pp. 237-242 ◽  
Author(s):  
Tahari Abdou El Karim ◽  
Bendakmousse Abdeslam ◽  
Ait Aoudia Samy
Keyword(s):  
Image Processing ◽  
Genetic Algorithms ◽  
Simulated Annealing ◽  
Image Registration ◽  
Cost Function ◽  
Population Genetic ◽  
Medical Image ◽  
Medical Image Registration ◽  
Anatomical Structures

The image registration is a very important task in image processing. In the field of medical imaging, it is used to compare the anatomical structures of two or more images taken at different time to track for example the evolution of a disease. Intensity-based techniques are widely used in the multi-modal registration. To have the best registration, a cost function expressing the similarity between these images is maximized. The registration problem is reduced to the optimization of a cost function. We propose to use neighborhood meta-heuristics (tabu search, simulated annealing) and a meta-heuristic population (genetic algorithms). An evaluation step is necessary to estimate the quality of registration obtained. In this paper we present some results of medical image registration

scholarly journals Coupling brain-tumor biophysical models and diffeomorphic image registration

2019 ◽  
Vol 347 ◽  
pp. 533-567 ◽  
Author(s):  
Klaudius Scheufele ◽  
Andreas Mang ◽  
Amir Gholami ◽  
Christos Davatzikos ◽  
George Biros ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Image Registration ◽  
Biophysical Models ◽  
Diffeomorphic Image Registration

Push Recovery Strategy of Dynamic Gait Transition between Walking, Running and Hopping

2019 ◽  
Vol 16 (03) ◽  
pp. 1940001 ◽  
Author(s):  
Takumi Kamioka ◽  
Hiroyuki Kaneko ◽  
Mitsuhide Kuroda ◽  
Chiaki Tanaka ◽  
Shinya Shirokura ◽  
...  
Keyword(s):  
Parallel Computing ◽  
Cost Function ◽  
Forward Direction ◽  
Planning Method ◽  
Recovery Strategy ◽  
External Disturbances ◽  
Gait Transition ◽  
Lateral Direction ◽  
Push Recovery ◽  
Dynamic Gait

Re-planning of gait trajectory is a crucial ability to compensate for external disturbances. To date, a large number of methods for re-planning footsteps and timing have been proposed. However, robots with the ability to change gait from walking to running or from walking to hopping were never proposed. In this paper, we propose a method for re-planning not only for footsteps and timing but also for the types of gait which consists of walking, running and hopping. The re-planning method of gait type consists of parallel computing and a ranking system with a novel cost function. To validate the method, we conducted push recovery experiments which were pushing in the forward direction when walking on the spot and pushing in the lateral direction when walking in the forward direction. Results of experiments showed that the proposed algorithm effectively compensated for external disturbances by making a gait transition.

Sign in / Sign up

Export Citation Format

Share Document