A semi-automatic method for segmentation of multiple sclerosis lesions on dual-echo magnetic resonance images

Loredana Storelli, Elisabetta Pagani, Maria Assunta Rocca, Mark A. Horsfield, Massimo Filippi

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

Abstract

The identification and segmentation of focal hyperintense lesions on magnetic resonance images (MRI) are essential steps in the assessment of disease burden in multiple sclerosis (MS) patients. Manual lesion segmentation is considered to be the gold standard, although it is time-consuming and has poor intra- and inter-operator reproducibility. Here, we present a segmentation method based on dual-echo MR images initialized by manual identification of lesions and a priori information. The classification technique is based on a region growing approach with a final segmentation refinement step. The results have revealed high similarity between the segmentation performed with this method and that performed manually by an expert operator, as well as a low misclassification of lesions. Moreover, the time required for segmentation is drastically reduced.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages80-90
Number of pages11
Volume9556
ISBN (Print)9783319308579
DOIs
Publication statusPublished - 2016
Event1st International Workshop on Brainlesion, Brainles 2015 Held in Conjunction with International Conference on Medical Image Computing for Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany
Duration: Oct 5 2015Oct 5 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9556
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other1st International Workshop on Brainlesion, Brainles 2015 Held in Conjunction with International Conference on Medical Image Computing for Computer-Assisted Intervention, MICCAI 2015
CountryGermany
CityMunich
Period10/5/1510/5/15

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Storelli, L., Pagani, E., Rocca, M. A., Horsfield, M. A., & Filippi, M. (2016). A semi-automatic method for segmentation of multiple sclerosis lesions on dual-echo magnetic resonance images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9556, pp. 80-90). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9556). Springer Verlag. https://doi.org/10.1007/978-3-319-30858-6_8