ISLES (SISS) challenge 2015: Segmentation of stroke lesions using spatial normalization, random forest classification and contextual clustering

Hanna Leena Halme*, Antti Korvenoja, Eero Salli

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

8 Citations (Scopus)

Abstract

Automated methods for segmentation of ischemic stroke lesions could significantly reduce the workload of radiologists and speed up the beginning of patient treatment. In this paper, we present a method for subacute ischemic stroke lesion segmentation from multispectral magnetic resonance images (MRI). The method involves classification of voxels with a Random Forest algorithm and subsequent classification refinement with contextual clustering. In addition, we utilize the training data to build statistical group-specific templates and use them for calculation of individual voxel-wise differences from the global mean. Our method achieved a Dice coefficient of 0.61 for the leave-one-out cross-validated training data and 0.47 for the testing data of the ISLES challenge 2015.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages211-221
Number of pages11
Volume9556
ISBN (Print)9783319308579
DOIs
Publication statusPublished - 2016
MoE publication typeA4 Article in a conference publication
EventInternational Workshop on Brainlesion - Munich, Germany
Duration: 5 Oct 20155 Oct 2015
Conference number: 1

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

Workshop

WorkshopInternational Workshop on Brainlesion
Abbreviated titleBrainles
CountryGermany
CityMunich
Period05/10/201505/10/2015

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  • Cite this

    Halme, H. L., Korvenoja, A., & Salli, E. (2016). ISLES (SISS) challenge 2015: Segmentation of stroke lesions using spatial normalization, random forest classification and contextual clustering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9556, pp. 211-221). (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_18