Edge intensity normalization as a bias field correction during balloon snake segmentation of breast MRI
Paper in proceedings, 2008

Segmentation of fat suppressed dynamic contrast enhanced MRI (DCE-MRI) image data can pose significant problems because of the inherently poor signal-to-noise ratio (SNR) and intensity variations due to the bias field. Segmentation methods such as balloon snakes, while able to operate in a poor SNR environment, are sensitive to variations in edge intensity, which are regularly encountered within DCE-MRI due to the bias field. In order to overcome the effects of the bias field, an intensity normalization based on the strength of the strongest edge, i.e. the skin-air-boundary, is proposed and evaluated. This normalization allows balloon segmentations to be run three times faster while maintaining, or even improving accuracy.

Author

Andrew Hill

Andrew Mehnert

Chalmers, Signals and Systems

Stuart Crozier

Proc. 2008 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

1557-170X (ISSN)

3040 - 3043

Areas of Advance

Life Science Engineering (2010-2018)

Subject Categories

Computer Vision and Robotics (Autonomous Systems)

Medical Image Processing

DOI

10.1109/IEMBS.2008.4649844

More information

Created

10/7/2017