Literature DB >> 24110443

An automatic brain tumor segmentation tool.

Idanis Diaz, Pierre Boulanger, Russell Greiner, Bret Hoehn, Lindsay Rowe, Albert Murtha.   

Abstract

This paper introduces an automatic brain tumor segmentation method (ABTS) for segmenting multiple components of brain tumor using four magnetic resonance image modalities. ABTS's four stages involve automatic histogram multi-thresholding and morphological operations including geodesic dilation. Our empirical results, on 16 real tumors, show that ABTS works very effectively, achieving a Dice accuracy compared to expert segmentation of 81% in segmenting edema and 85% in segmenting gross tumor volume (GTV).

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Year:  2013        PMID: 24110443     DOI: 10.1109/EMBC.2013.6610256

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

1.  Iterative probabilistic voxel labeling: automated segmentation for analysis of The Cancer Imaging Archive glioblastoma images.

Authors:  T C Steed; J M Treiber; K S Patel; Z Taich; N S White; M L Treiber; N Farid; B S Carter; A M Dale; C C Chen
Journal:  AJNR Am J Neuroradiol       Date:  2014-11-20       Impact factor: 3.825

Review 2.  Automatic brain lesion segmentation on standard magnetic resonance images: a scoping review.

Authors:  Emilia Gryska; Justin Schneiderman; Isabella Björkman-Burtscher; Rolf A Heckemann
Journal:  BMJ Open       Date:  2021-01-29       Impact factor: 2.692

3.  Three-dimensional visualization of brain tumor progression based accurate segmentation via comparative holographic projection.

Authors:  Rania M Abdelazeem; Doaa Youssef; Jala El-Azab; Salah Hassab-Elnaby; Mostafa Agour
Journal:  PLoS One       Date:  2020-07-30       Impact factor: 3.240

  3 in total

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