Combining outlier detection with random walker for automatic brain tumor segmentation

Vasileios G. Kanas, Evangelia I. Zacharaki, Evangelos Dermatas, Anastasios Bezerianos, Kyriakos Sgarbas, Christos Davatzikos

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

Abstract

The diagnosis of brain neoplasms has been facilitated by the emerging of high-quality imaging techniques, such as Magnetic Resonance Imaging (MRI), while the combination of several sequences from conventional and advanced protocols has increased the diagnostic information. Treatment planning and therapy follow-up require the detection of neoplastic and edematous tissue boundaries, a very time consuming task when manually performed by medical experts based on the 3D MRI data. Automating the detection process is challenging, due to the high diversity in appearance of neoplastic tissue among different patients and, in many cases, similarity between neoplastic and normal tissue. In this paper, we propose an automatic brain tumor segmentation method based on a multilabel multiparametric random walks approach initialized by an outlier detection scheme. Segmentation assessment is performed by measuring spatial overlap between automatic segmentation and manual segmentation performed by medical experts. Good agreement is observed in most of the 26 cases for both neoplastic and edematous tissue. The highest achieved overlapping values were 0.74 and 0.79 for neoplastic and edematous tissue, respectively.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence Applications and Innovations - AIAI 2012 International Workshops
Subtitle of host publicationAIAB, AIeIA, CISE, COPA, IIVC, ISQL, MHDW, and WADTMB, Proceedings
PublisherSpringer New York LLC
Pages26-35
Number of pages10
EditionPART 2
ISBN (Print)9783642334115
DOIs
StatePublished - 2012
Event8th International Workshop on Artificial Intelligence Applications and Innovations, AIAI 2012: AIAB, AIeIA, CISE, COPA, IIVC, ISQL, MHDW, and WADTMB - Halkidiki, Greece
Duration: Sep 27 2012Sep 30 2012

Publication series

NameIFIP Advances in Information and Communication Technology
NumberPART 2
Volume382 AICT
ISSN (Print)1868-4238

Other

Other8th International Workshop on Artificial Intelligence Applications and Innovations, AIAI 2012: AIAB, AIeIA, CISE, COPA, IIVC, ISQL, MHDW, and WADTMB
CountryGreece
CityHalkidiki
Period9/27/129/30/12

Keywords

  • brain neoplasms
  • k- means
  • magnetic resonance imaging
  • outlier detection
  • random walks
  • segmentation

ASJC Scopus subject areas

  • Information Systems and Management

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  • Cite this

    Kanas, V. G., Zacharaki, E. I., Dermatas, E., Bezerianos, A., Sgarbas, K., & Davatzikos, C. (2012). Combining outlier detection with random walker for automatic brain tumor segmentation. In Artificial Intelligence Applications and Innovations - AIAI 2012 International Workshops: AIAB, AIeIA, CISE, COPA, IIVC, ISQL, MHDW, and WADTMB, Proceedings (PART 2 ed., pp. 26-35). (IFIP Advances in Information and Communication Technology; Vol. 382 AICT, No. PART 2). Springer New York LLC. https://doi.org/10.1007/978-3-642-33412-2_3