scholarly journals Evaluation Method for the Optimization of 3D Rigid Image Registration on Multimodal Image Datasets

2019 ◽  
Vol 9 (1) ◽  
pp. 5539-5545
Keyword(s):  
Computed Tomography ◽  
Image Registration ◽  
Mutual Information ◽  
Planning System ◽  
Treatment Planning System ◽  
Mean Square ◽  
Similarity Metric ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
Image Datasets

Optimization based three dimensional (3D) rigid image registration (RIR) is one of the most commonly used methods of image registration in radiotherapy. Interpolator and similarity metric plays a crucial role in optimization image registration process. In this paper, the efficiency of image registration algorithm is analyzed by using various combinations of interpolators and similarity metric in terms of quantitative measures and is compared with commercially available image registration algorithm in radiotherapy. Computed Tomography (CT) and Cone Beam Computed Tomography (CBCT) image datasets were registered by image registration algorithm written in python language using simple image tool kit (SITK). Different combinations of similarity metric and interpolator such as mean square difference (MSD), mutual information (MI), demons and nearest neighbor (NN), linear, B- spline respectively were used in this study. The efficiency of the algorithm was quantified in terms of mean square error (MSE), structural similarity index (SSI), normalized cross correlation (NCC) and mutual information (MI). The image registration algorithm with most efficient combination of similarity metric and interpolator was selected for comparison with the commercially available image registration algorithm. The algorithm for multimodal (CTCBCT) 3D image registration with NN interpolator and MI similarity metric showed the highest values of SSI, NCC and MI as 0.865, 0.933, 1.223 respectively among other combination of interpolator and similarity metric. Further this algorithm when compared and statistically analyzed with commercially available image registration algorithm of Treatment Planning System (TPS. most commonly used for radiotherapy treatment) resulted in no significant difference (F value NCC-3.18, MI-4.010, SSI2.776) in their quantitative measures. The present study is limited to 3D RIR and can be extended for deformable image registration.

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.

Effect of Measure and Interpolation Methods for Intensity-Based Medical Image Registration

2013 ◽  
Vol 647 ◽  
pp. 612-617
Author(s):  
Guo Dong Zhang ◽  
Xiao Hu Xue ◽  
Wei Guo
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Medical Image ◽  
Medical Image Registration ◽  
Registration Accuracy ◽  
Partial Volume ◽  
Interpolation Methods ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
Local Extreme

The local extreme is main reason to hamper the optimization process and influence the registration accuracy in medical image registration algorithm. In general, the accuracy of image registration based on mutual information is afforded by interpolation methods. In this paper, we analyze the effect of the measure and interpolation methods for medical image registration and present a medical image registration algorithm using mutual strictly concave function measure and partial volume (PV) interpolation methods. The experiment results show that for images with low local correlation the algorithm has the ability to reduce the local extreme, the registration accuracy is improved, and the algorithm expended less time than mutual information based registration method with partial volume (PV) or generalized partial volume estimation (GPVE).

scholarly journals Analysis of Image Features and TCM Syndrome Types of Lobar Pneumonia in Children Based on Mean Square Deviation Lung CT Image Registration Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Shuang Wang ◽  
Yi Zhang ◽  
Yongkun Liu
Keyword(s):  
Image Registration ◽  
Ct Image ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Lobar Pneumonia ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
The Common ◽  
Tcm Syndrome ◽  
Lung Ct

The aim was to analyze the application of computed tomography (CT) images in the diagnosis of lesions, and the composition of traditional Chinese medicine (TCM) syndromes in children with lobar pneumonia. Lung CT image registration algorithm was constructed based on optimized mean square deviation (OMSD) algorithm, which was applied to CT images of 188 children patients with lobar pneumonia before and after treatment. Besides, free-form deformation (FFD) algorithm and mean square deviation (MSD) algorithm were introduced for comparison with OMSD. Results showed that sum of squared differences (SSD) of OMSD was significantly lower than that of MSD and FFD ( P < 0.05 ). The mutual information (MI), relative overlap rate (ROR), and rcc of OMSD were markedly higher than those of MSD and FFD ( P < 0.05 ). After treatment, the number of pulmonary interstitial thickening, lobular interstitial thickening, ground-glass shadow, patchy shadow, consolidation shadow, pleural thickening, pleural effusion, lymphadenopathy, pneumothorax, and mediastinal emphysema decreased sharply in contrast to before treatment ( P < 0.05 ). Among the selected children, there were 184 children patients with empirical TCM syndrome, accounting for 97.85%, and its dominant syndrome was wind-heat closed lung syndrome (52.75%) and phlegm-heat closed lung syndrome (46.11%). The main symptoms of wind-heat closed and phlegm-heat closed lung syndrome were fever, cough, and pulmonary rales. In conclusion, OMSD was superior to MSD and FFD in lung CT image registration. CT registration image based on OMSD could clearly display the intrapulmonary and extrapulmonary manifestations of children patients, so as to enhance the clinical diagnosis effect. Besides, wind-heat closed lung syndrome and phlegm-heat closed lung syndrome were the common types of TCM syndrome of children pneumonia with the common symptoms of fever and cough.

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