Infrared image non-rigid registration based on regional information entropy demons algorithm

2015 ◽  
Author(s):  
Chaoliang Lu ◽  
Lihua Ma ◽  
Ming Yu ◽  
Shumin Cui ◽  
Qingrong Wu
Keyword(s):  
Information Entropy ◽  
Infrared Image ◽  
Rigid Registration ◽  
Demons Algorithm

scholarly journals ACCELERATING 3D NON-RIGID REGISTRATION USING GRAPHICS HARDWARE

2008 ◽  
Vol 08 (01) ◽  
pp. 81-98 ◽  
Author(s):  
NICOLAS COURTY ◽  
PIERRE HELLIER
Keyword(s):  
Image Analysis ◽  
Classical Method ◽  
Graphics Hardware ◽  
Processing Unit ◽  
Recursive Filtering ◽  
Rigid Registration ◽  
Guided Surgery ◽  
Graphical Processing Unit Implementation ◽  
Demons Algorithm ◽  
Graphical Processing

There is an increasing need for real-time implementation of 3D image analysis processes, especially in the context of image-guided surgery. Among the various image analysis tasks, non-rigid image registration is particularly needed and is also computationally prohibitive. This paper presents a GPU (Graphical Processing Unit) implementation of the popular Demons algorithm using a Gaussian recursive filtering. Acceleration of the classical method is mainly achieved by a new filtering scheme on GPU which could be reused in or extended to other applications and denotes a significant contribution to the GPU-based image processing domain. This implementation was able to perform a non-rigid registration of 3D MR volumes in less than one minute, which corresponds to an acceleration factor of 10 compared to the corresponding CPU implementation. This demonstrated the usefulness of such method in an intra-operative context.

GRID-ENABLED NON-RIGID REGISTRATION OF MEDICAL IMAGES

2004 ◽  
Vol 14 (02) ◽  
pp. 197-216 ◽  
Author(s):  
RADU STEFANESCU ◽  
XAVIER PENNEC ◽  
NICHOLAS AYACHE
Keyword(s):  
High Performance ◽  
Cluster Computing ◽  
Parallel Implementation ◽  
Low Cost ◽  
Computation Time ◽  
Clinical Environment ◽  
Healthcare Organizations ◽  
Rigid Registration ◽  
Demons Algorithm ◽  
Point To Point

Over recent years, non-rigid registration has become a major issue in medical imaging. It consists in recovering a dense point-to-point correspondence field between two images, and usually takes a long time. This is in contrast to the needs of a clinical environment, where usability and speed are major constraints, leading to the necessity of reducing the computation time from slightly less than an hour to just a few minutes. As financial pressure makes it hard for healthcare organizations to invest in expensive high-performance computing (HPC) solutions, cluster computing proves to be a convenient solution to our computation needs, offering a large processing power at a low cost. Among the fast and efficient non-rigid registration methods, we chose the demons algorithm for its simplicity and good performances. The parallel implementation decomposes the correspondence field into spatial blocks, each block being assigned to a node of the cluster. We obtained an acceleration of 11 by using 15 2GHz PC's connected through a 1GB/s Ethernet network and reduced the computation time from 40min to 3min30. In order to further optimize the costs and the maintenance load, we investigate in the second part the transparent use of shared computing resources, either through a graphic client or a Web one.

Regional information entropy Demons for infrared image nonrigid registration

Optik ◽  
2016 ◽  
Vol 127 (1) ◽  
pp. 227-231 ◽  
Author(s):  
Lu Chaoliang ◽  
Ma Lihua ◽  
Yu min ◽  
Cui Shumin
Keyword(s):  
Information Entropy ◽  
Infrared Image ◽  
Nonrigid Registration

scholarly journals An Effective Non-rigid Registration Approach for Ultrasound Image Based On “Demons” Algorithm

2012 ◽  
Vol 26 (3) ◽  
pp. 521-529 ◽  
Author(s):  
Yan Liu ◽  
H. D. Cheng ◽  
Jianhua Huang ◽  
Yingtao Zhang ◽  
Xianglong Tang ◽  
...  
Keyword(s):  
Ultrasound Image ◽  
Rigid Registration ◽  
Demons Algorithm

scholarly journals Incorporating Metric Flows and Sparse Jacobian Transformations in ITK

2006 ◽  
Author(s):  
Mathieu De craene ◽  
Aloys Du bois d'aische ◽  
Benoit Macq ◽  
Simon Warfield
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Computation Time ◽  
Deformable Registration ◽  
Deformation Field ◽  
Transformation Model ◽  
Rigid Registration ◽  
Information Metric ◽  
Demons Algorithm

Various metrics have been proposed in the literature for performing intrinsic automatic image to image registration. Among these measures, mutual information is a very popular one because of its robustness and accuracy for a wide variety of applications. In this paper, we propose a filter for performing non-rigid registration by estimating a dense deformation field derived from the mutual information metric. This filter takes place in the ITK PDE deformable registration design like the Demons algorithm of Thirion. We also show how the concept of metric flow is conceptually linked to the concept of metric derivative for a prior transformation model by the transformation jacobian. We also suggest a sparse implementation of the GetJacobian() method for reducing the computation time of a metric derivative for local transformations models.

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