Coupled dictionary learning for automatic multi-label brain tumor segmentation in flair MRI images

Saif Dawood Salman Al-Shaikhli*, Michael Ying Yang, Bodo Rosenhahn

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

Brain tumor segmentation and labeling is a challenging task in medical imaging. In this paper, a novel patch based dictionary learning algorithm for automatic multi-label brain tumor segmentation is proposed. Based on image reconstruction, we present coupled dictionaries, one dictionary of grayscale brain tumor image patches and one dictionary of tumor labels, which can then be used for automatic multi-label brain tumor segmentation of a test image data. The dictionaries are learned from training images of BraTS-MICCAI and the SPL/NSG brain tumor databases. The label dictionary is proposed to select foreground and background labels for automatic graph-cut segmentation. For quantitative evaluation, five different metric scores are computed using the online evaluation tool provided by the BraTS organizers. Experimental results demonstrate that the proposed approach achieves accurate results and outperforms most of the state-of-the-art methods cited in BraTS-MICCAI challenge.

Original languageEnglish
Title of host publicationAdvances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings
EditorsJason Jerald, George Bebis, Bahram Parvin, Zhigang Deng, Richard Boyle, El Choubassi Maha, Hui Zhang, Darko Koracin, Ryan McMahan, Steven M. Drucker, Mark Carlson, Kambhamettu Chandra
Place of PublicationLas Vegas
PublisherSpringer Verlag
Pages489-500
Number of pages12
ISBN (Electronic)9783319142487
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event10th International Symposium on Visual Computing, ISVC 2014 - Las Vegas, United States
Duration: 8 Dec 201410 Dec 2014
Conference number: 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8887
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Symposium on Visual Computing, ISVC 2014
Abbreviated titleISVC
CountryUnited States
CityLas Vegas
Period8/12/1410/12/14

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