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A fast algorithm for medical image segmentation based on improved incremental variational level set

  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publication2009 IEEE Intrumentation and Measurement Technology Conference, I2MTC 2009
Pages442-445
Number of pages4
DOIs
StatePublished - 2009
Event2009 IEEE Intrumentation and Measurement Technology Conference, I2MTC 2009 - Singapore, Singapore
Duration: 5 May 20097 May 2009

Publication series

Name2009 IEEE Intrumentation and Measurement Technology Conference, I2MTC 2009

Conference

Conference2009 IEEE Intrumentation and Measurement Technology Conference, I2MTC 2009
Country/TerritorySingapore
CitySingapore
Period5/05/097/05/09

Keywords

  • Chan-Vese model
  • Level set
  • Medical image segmentation

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