Interactive semi-automated method using non-negative matrix factorization and level set segmentation for the BRATS challenge

Dimah Dera, Fabio Raman, Nidhal Bouaynaya, Hassan M. Fathallah-Shaykh

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

1 Scopus citations

Abstract

The 2016 BRATS includes imaging data on 191 patients diagnosed with low and high grade gliomas. We present a novel method for multimodal brain segmentation, which consists of (1) an automated, accurate and robust method for image segmentation, combined with (2) semi-automated and interactive multimodal labeling. The image segmentation applies Non-negative Matrix Factorization (NMF), a decomposition technique that reduces the dimensionality of the image by extracting its distinct regions. When combined with the level-set method (LSM), NMF-LSM has proven to be an efficient method for image segmentation. Segmentation of the BRATS images by NMF-LSM is computed by the Cheaha supercomputer at the University of Alabama at Birmingham. The segments of each image are ranked by maximal intensity. The interactive labeling software, which identifies the four targets of the challenge, is semi-automated by cross-referencing the normal segments of the brain across modalities.

Original languageEnglish (US)
Title of host publicationBrainlesion
Subtitle of host publicationGlioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Second International Workshop, BrainLes 2016, with the Challenges on BRATS, ISLES and mTOP 2016 Held in Conjunction with MICCAI 2016, Revised Selected Papers
EditorsBjoern Menze, Mauricio Reyes, Alessandro Crimi, Oskar Maier, Stefan Winzeck, Heinz Handels
PublisherSpringer Verlag
Pages192-205
Number of pages14
ISBN (Print)9783319555232
DOIs
StatePublished - Jan 1 2016
Event2nd International Workshop on Brain Lesion, BrainLes 2016, with the challenges on Brain Tumor Segmentation BRATS, Ischemic Stroke Lesion Image Segmentation ISLES, and the Mild Traumatic Brain Injury Outcome Prediction mTOP held in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece
Duration: Oct 17 2016Oct 17 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10154 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Workshop on Brain Lesion, BrainLes 2016, with the challenges on Brain Tumor Segmentation BRATS, Ischemic Stroke Lesion Image Segmentation ISLES, and the Mild Traumatic Brain Injury Outcome Prediction mTOP held in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
CountryGreece
City Athens
Period10/17/1610/17/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Dera, D., Raman, F., Bouaynaya, N., & Fathallah-Shaykh, H. M. (2016). Interactive semi-automated method using non-negative matrix factorization and level set segmentation for the BRATS challenge. In B. Menze, M. Reyes, A. Crimi, O. Maier, S. Winzeck, & H. Handels (Eds.), Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Second International Workshop, BrainLes 2016, with the Challenges on BRATS, ISLES and mTOP 2016 Held in Conjunction with MICCAI 2016, Revised Selected Papers (pp. 192-205). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10154 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-55524-9_19