Research on non rigid registration algorithm of DCE-MRI based on mutual information and optical flow

2015 ◽  
Author(s):  
Shihua Yu ◽  
Rui Wang ◽  
Kaiyu Wang ◽  
Mengmeng Xi ◽  
Jiashuo Zheng ◽  
...  
Keyword(s):  
Mutual Information ◽  
Optical Flow ◽  
Dce Mri ◽  
Rigid Registration ◽  
Registration Algorithm

Research on the Topology Preservation of the Demons Non-rigid Registration Algorithm

2010 ◽  
Vol 36 (1) ◽  
pp. 179-183
Author(s):  
Xiang-Bo LIN ◽  
Tian-Shuang QIU ◽  
Su RUAN ◽  
NICOLIER Frédéric
Keyword(s):  
Topology Preservation ◽  
Rigid Registration ◽  
Registration Algorithm

scholarly journals Automatic PET-CT Image Registration Method Based on Mutual Information and Genetic Algorithms

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Martina Marinelli ◽  
Vincenzo Positano ◽  
Francesco Tucci ◽  
Danilo Neglia ◽  
Luigi Landini
Keyword(s):  
Mutual Information ◽  
Optimization Method ◽  
Global Maximum ◽  
Similarity Function ◽  
Spatial Transformation ◽  
Registration Method ◽  
Registration Algorithm ◽  
Positron Emission ◽  
Pet Ct ◽  
Artery Disease

Hybrid PET/CT scanners can simultaneously visualize coronary artery disease as revealed by computed tomography (CT) and myocardial perfusion as measured by positron emission tomography (PET). Manual registration is usually required in clinical practice to compensate spatial mismatch between datasets. In this paper, we present a registration algorithm that is able to automatically align PET/CT cardiac images. The algorithm bases on mutual information (MI) as registration metric and on genetic algorithm as optimization method. A multiresolution approach was used to optimize the processing time. The algorithm was tested on computerized models of volumetric PET/CT cardiac data and on real PET/CT datasets. The proposed automatic registration algorithm smoothes the pattern of the MI and allows it to reach the global maximum of the similarity function. The implemented method also allows the definition of the correct spatial transformation that matches both synthetic and real PET and CT volumetric datasets.

SAR Image Registration Using Ratio Mutual Information

2012 ◽  
Vol 241-244 ◽  
pp. 2630-2637
Author(s):  
Chun Rong Wei ◽  
Chu He ◽  
Hong Sun
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Speckle Noise ◽  
Synthetic Aperture Radar Image ◽  
Reference Image ◽  
Sar Image ◽  
Local Maxima ◽  
Characteristic Quantity ◽  
Registration Algorithm ◽  
Image Registration Algorithm

In order to reduce the noise sensitivity of the SAR (synthetic aperture radar) image registration, a image registration algorithm which basing on the ratio mutual information (RatioMI) is proposed in this paper. Firstly, the ratio images of the reference image and the floating image are gotten by using the ratio operator, and then take the two ratio images as a similar characteristic quantity to construct the similarity measure function which was used in the optimization process of the image registration experiment. The experimental results of the SAR image registration show that the new registration algorithm which based on the RatioMI is effectively in avoiding the local maxima point problems causing by speckle noise.

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