Subjects: Medicine, Pharmacy >> Preclinical Medicine submitted time 2018-06-15 Cooperative journals: 《南方医科大学学报》
Abstract： Objective To achieve low-dose digital breast tomosynthsis (DBT) projection recovery using penalized weighted least square algorithm incorporating accurate modeling of the variance of the projection data and noise correlation in the flat panel detector. Methods Models were established for the quantal noise and electronic noise in the DBT system to construct the penalized weighted least squares algorithm based on noise correlation for projection data restoration. The filter back projection algorithm was then used for DBT image reconstruction. Results The reconstruction results of the ACR phantom data at different dose levels showed a good performance of the proposed method in noise suppression and detail preservation. CNRs and LSNRs of the reconstructed images from the restored projections were increased by about 3.6 times compared to those of reconstructed images from the original projections. Conclusion The proposed method can significantly reduce noise and improve the quality of DBT images.
Subjects: Medicine, Pharmacy >> Preclinical Medicine submitted time 2018-06-15 Cooperative journals: 《南方医科大学学报》
Abstract： Objective We purpose a novel factor analysis method based on kinetic cluster and α-divergence measure for extracting the blood input function and the time-activity curve of the regional tissue from dynamic myocardial positron emission computed tomography(PET) images. Methods Dynamic PET images were decomposed into initial factors and factor images by minimizing the α-divergence between the factor model and actual image data. The kinetic clustering as a priori constraint was then incorporated into the model to solve the nonuniqueness problem, and the tissue time-activity curves and the tissue space distributions with physiological significance were generated. Results The model was applied to the 82RbPET myocardial perfusion simulation data and compared with the traditional model-based least squares measure and the minimal spatial overlap constraint. The experimental results showed that the proposed model performed better than the traditional model in terms of both accuracy and sensitivity. Conclusion This method can select the optimal measure by α value, and incorporate the prior information of the kinetic clustering of PET image pixels to obtain the accurate time-activity curves of the tissue, which has shown good performance in visual evaluation and quantitative evaluation.
Subjects: Medicine, Pharmacy >> Preclinical Medicine submitted time 2018-01-25 Cooperative journals: 《南方医科大学学报》
Abstract： Objective We purpose a novel factor analysis method based on kinetic cluster and α-divergence measure for extracting the blood input function and the time-activity curve of the regional tissue from dynamic myocardial positron emission computed tomography(PET) images. Methods Dynamic PET images were decomposed into initial factors and factor images by minimizing the α-divergence between the factor model and actual image data. The kinetic clustering as a priori constraint was then incorporated into the model to solve the nonuniqueness problem, and the tissue time-activity curves and the tissue space distributions with physiological significance were generated. Results The model was applied to the 82RbPET myocardial perfusion simulation data and compared with the traditional model-based least squares measure and the minimal spatial overlap constraint. The experimental results showed that the proposed model performed better than the traditional model in terms of both accuracy and sensitivity. Conclusion This method can select the optimal measure by α value, and incorporate the prior information of the kinetic clustering of PET image pixels to obtain the accurate time-activity curves of the tissue,whichhasshowngoodperformanceinvisualevaluationandquantitativeevaluation.
Subjects: Medicine, Pharmacy >> Preclinical Medicine submitted time 2017-12-07 Cooperative journals: 《南方医科大学学报》
Abstract： Objective We propose a multi-weighted probabilistic atlas to obtain accurate, robust, and reliable segmentation. The local similarity measure is used as the weight to compute the probabilistic atlas, and the distance field is used as the weight to incorporate the locality information of the atlas; the self-similarity is used as the weight to incorporate the local information of target image to refine the probabilistic atlas. Experimental results with brain MRI images showed that the proposed algorithm outperforms the common brain image segmentation methods and achieved a median Dice coefficient of 87.1% on the left hippocampus and 87.6% on the right.
Subjects: Medicine, Pharmacy >> Preclinical Medicine submitted time 2017-12-07 Cooperative journals: 《南方医科大学学报》
Abstract： Objective We propose a cross-correlation method for automatic extraction of the pennation angle (PA) of the gastrocnemius (GM) muscle from ultrasound radiofrequency (RF) signals. Methods The ultrasound RF signals of the GM muscles in tension condition from normal subjects and the simulated ultrasound signals were collected. After the starting point of tracking, a fascicle was selected in the reconstructed GM ultrasound image from the RF signals, and the fascicle and deep aponeurosis could be automatically tracked using the cross-correlation algorithm. The lines of the fascicle and deep aponeurosis were then drawn and the PA was calculated. The reproducibility of the proposed method and its consistency with the manual measurement method were tested. Results The angles of the simulated fascicles were precisely extracted automatically. The difference between the experimental measurement and the theoretical values was less than 1� The PA measured automatically and manually was 20.48氨0.47�and 21.49氨1.79� respectively. The coefficient of variation (CV) of the two methods was less than 3% and the root-mean square error (RMSE) was less than 1� Bland-Altman plot showed a good agreement between the proposed automatic method and the manual method. Conclusion The proposed cross-correlation automatic measurement method can detect the orientation of the fascicle and deep aponeurosis and measure the PA based on ultrasound RF signals with serious speckle noise.
Hits
Hits
Downloads
Comment