An improved Gaussian mixture modeling algorithm combining foreground matching and short-term stability measure for motion detection

2019 ◽  
Vol 79 (11-12) ◽  
pp. 7049-7071
Author(s):  
Chao Zhang ◽  
Xiaopei Wu ◽  
Xiangping Gao
Keyword(s):  
Motion Detection ◽  
Gaussian Mixture ◽  
Mixture Modeling ◽  
Short Term ◽  
Term Stability ◽  
Stability Measure ◽  
Gaussian Mixture Modeling ◽  
Modeling Algorithm

scholarly journals Thresholding techniques for segmentation of atherosclerotic plaque and lumen areas in vascular arteries

2015 ◽  
Vol 63 (1) ◽  
pp. 269-280 ◽  
Author(s):  
T. Markiewicz ◽  
M. Dziekiewicz ◽  
S. Osowski ◽  
M. Maruszynski ◽  
W. Kozlowski ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Blood Vessel ◽  
Atherosclerotic Plaque ◽  
Gaussian Mixture ◽  
Mixture Modeling ◽  
Automatic Evaluation ◽  
Atherosclerosis Progression ◽  
Vessel Area ◽  
Gaussian Mixture Modeling ◽  
Automatic Methods

Abstract The paper develops the automatic methods of segmentation of the blood vessel area in the images of the multi-slice computed tomography, allowing to separate the lumen from the atherosclerotic plaque areas. The solution is based on the application of different implementations of thresholding, including between class variance in a bimodal mode, Gaussian mixture modeling, clustering technique, polynomial and multilayer perceptron approximations. These methods are compared with many examples of arteries of different percentage of the plaque occupancy in the iliac and femoral arteries. The numerical results of segmentation have been verified by the medical experts and prove its usefulness in medical practice. The presented system can find application in an automatic evaluation of the atherosclerosis progression/regression of patients on the basis of sequence of Computed Tomography slice images.

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