Superpixel-based segmentation of glioblastoma multiforme from multimodal MR images

Po Su, Jianhua Yang, Hai Li, Linda Chi, Zhong Xue, Stephen T. Wong

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

10 Scopus citations

Abstract

Due to complex imaging characteristics such as large diversity in shapes and appearances combining with deformation of surrounding tissues, it is a challenging task to segment glioblastoma multiforme (GBM) from multimodal MR images. In particular, it is important to capture the heterogeneous features of enhanced tumor, necrosis, and non-enhancing T2 hyperintense regions (T2HI) to determine the aggressiveness of the tumor from neuroimaging. In this paper, we propose a superpixel-based graph spectral clustering method to improve the robustness of GBM segmentation. A new graph spectral clustering algorithm is designed to group superpixels to different tissue types. First, a local k-means clustering with weighted distances is employed to segment the MR images into a number of homogeneous regions, called superpixels. Then, the spectral clustering algorithm is utilized to extract the enhanced tumor, necrosis, and T2HI by considering the superpixel map as a graph. Experiment results demonstrate better performance of the proposed method by comparing with pixel-based and the normalized cut segmentation methods.

Original languageEnglish (US)
Title of host publicationMultimodal Brain Image Analysis - Third International Workshop, MBIA 2013, Held in Conjunction with MICCAI 2013, Proceedings
Pages74-83
Number of pages10
DOIs
StatePublished - 2013
Event3rd International Workshop on Multimodal Brain Image Analysis, MBIA 2013, Held in Conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan
Duration: Sep 22 2013Sep 22 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8159 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Workshop on Multimodal Brain Image Analysis, MBIA 2013, Held in Conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013
CountryJapan
CityNagoya
Period9/22/139/22/13

Keywords

  • GBM
  • multimodal MR images
  • spectral clustering
  • superpixel

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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