Narrow band region-scalable fitting model for image segmentation in the presence of intensity inhomogeneities

Bei Yan, Chunming Li, Mei Xie, Christos Davatzikos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a modified region-scalable fitting (RSF) model in [1] and a more efficient narrow band algorithm to perform level set evolution. A distance regularization term is used to maintain the regularity of the level set function, which is necessary for maintaining stable level set evolution and ensuring accurate numerical computation. The computational efficiency of our algorithm is further improved by using 1D directional convolutions to approximate the 2D convolutions in the computation of the two fitting functions in the RSF model. Our algorithm has been tested on synthetic and real medical images with promising results.

Original languageEnglish (US)
Title of host publication2011 8th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI'11
Pages1994-1997
Number of pages4
DOIs
StatePublished - Nov 2 2011
Event2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States
Duration: Mar 30 2011Apr 2 2011

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
Country/TerritoryUnited States
CityChicago, IL
Period3/30/114/2/11

Keywords

  • Image segmentation
  • Intensity inhomogeneity
  • Level set
  • Narrow band
  • Region-scalable fitting

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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