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Application of Improved GVF Snake Algorithm in Lung Cancer Detection Tectnology

Author: WangRuiZuo
Tutor: GuoXiJuan
School: Yanshan University
Course: Computer Software and Theory
Keywords: Image Segmentation Automatic detection GVF Snake Bowls Law Over-segmentation Leakage split
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 79
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Abstract


Lungs automatic image segmentation techniques for reducing the missed diagnosis and misdiagnosis of clinical significance. The lung segmentation extracted lung images in the lung parenchyma , lung tumor characteristics given lung tumor segmentation of images to help doctors analyze and judge . Extraction of lung images of lung parenchyma in the lungs automatic image segmentation system have important significance . First, through the analysis of the existing the lungs automatic detection technology for active contour models can not solve deep depression problem GVF Snake algorithm based on improved energy formula . By introducing the lungs , such as gradient and curvature of the image information , and , in their common joint effect , improved energy formula , to determine the lung image boundary , to solve the problem of a deep depression can not be divided at the active contour algorithm . Second , improve energy formula active contour curves stop conditions will change for Improved GVF Sanke algorithm , active contour curve will not be able to stop , and crossed the real border convergence point phenomenon is given by the gradient information and the curvature information guidance direction of the external force . Introduced symbolic function reset curve movement stop condition to solve the problems of the curve can not converge to the true boundary . The active contour curves stop the re- setting of the conditions improve lung image segmentation speed and reduce the time complexity of the algorithm . Pleura adhesions lung tumor segmentation the lung image boundary discontinuous or continuous but a far cry from a real lung image boundary leakage segmentation problem , proposed adaptive border marching algorithm . The algorithm geometrically smooth lung boundary , leakage segmentation problem solve of pulmonary adhesions tumor in the lungs image . Finally, the original image segmentation on computed tomography simulation experiments . Analysis of the existing problems in the lungs image segmentation algorithm , based on a large number of experiments , and provide direction for further research and valuable experience .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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