Automatic correction of bias field in magnetic resonance images

María Garza-Jinich, Verónica Medina, Oscar Yañez, Peter Meer

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

3 Scopus citations

Abstract

Two fully automatic restoration-segmentation algorithms are proposed for the processing of biased magnetic resonance images. A first approach is based on an expectation-maximization procedure, where the initial conditions for the class distribution parameters and the number of classes are obtained, without any a priori knowledge, from a mode-based analysis of the biased image. A second approach relies completely on the mode-based analysis to update the number of classes and distribution parameters in every iteration. Both methods give accurate results even for overlapping distributions distorted by a gain factor of up to 40%. The possibility of having automatic initial conditions provides an important enhancement to previously reported methods.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Image Analysis and Processing, ICIAP 1999
Pages752-756
Number of pages5
DOIs
StatePublished - 1999
Event10th International Conference on Image Analysis and Processing, ICIAP 1999 - Venice, Italy
Duration: Sep 27 1999Sep 29 1999

Publication series

NameProceedings - International Conference on Image Analysis and Processing, ICIAP 1999

Other

Other10th International Conference on Image Analysis and Processing, ICIAP 1999
Country/TerritoryItaly
CityVenice
Period9/27/999/29/99

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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