Title :
A fast algorithm for medical image segmentation based on improved incremental variational level set
Author :
Yi Shen ; Chunhui Zhu ; Qiang Wang ; Jiasheng Hao
Author_Institution :
Dept. of Control Sci. & Eng., Harbin Inst. of Technol., Harbin, China
Abstract :
According to the low calculating speed of Chan-Vese model for image segmentation caused by the iteration in process of evolution in the whole image region, a fast medical image segmentation method based on improved incremental variational level set is presented in this paper, in which incremental mode is adopted to get average gray value in iteration and a progressive iterative formula is used as the modification of analytical formula, so that some fast algorithms such as narrowband method could be applied to increase the efficiency of segmentation which makes the model more practical.
Keywords :
image segmentation; iterative methods; medical image processing; variational techniques; Chan-Vese model; gray value; improved incremental variational level set; iteration; medical image segmentation; narrowband method; progressive iterative formula; Algorithm design and analysis; Biomedical imaging; Deformable models; Image analysis; Image segmentation; Instrumentation and measurement; Level set; Medical diagnostic imaging; Narrowband; Topology; Chan-Vese model; level set; medical image segmentation;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2009. I2MTC '09. IEEE
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-3352-0
DOI :
10.1109/IMTC.2009.5168489