Improved tissue segmentation by including an MR acquisition model

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

1 Citation (Scopus)

Abstract

This paper presents a new MR tissue segmentation method. In contrast to most previous methods the image formation model includes the point spread function of the image acquisition. This allows optimal combination of images acquired with different contrast weighting, resolutions, and orientations. The proposed method computes the regularized maximum likelihood partial volume segmentation from the images. The quality the resulting segmentation is studied with a simulation experiment and by testing the reproducibility of the segmentation on repeated brain MRI scans. Our results demonstrate improved segmentation quality, especially at tissue edges.

Original languageEnglish
Title of host publicationMultimodal Brain Image Analysis - First International Workshop, MBIA 2011, Held in Conjunction with MICCAI 2011, Proceedings
Pages152-159
Number of pages8
DOIs
Publication statusPublished - 2011
Event1st International Workshop on Multimodal Brain Image Analysis, MBIA 2011, in Conjunction with the 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011 - Toronto, ON, Canada
Duration: 18 Sept 201118 Sept 2011

Publication series

SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7012 LNCS
ISSN0302-9743

Conference

Conference1st International Workshop on Multimodal Brain Image Analysis, MBIA 2011, in Conjunction with the 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
Country/TerritoryCanada
CityToronto, ON
Period18/09/1118/09/11

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