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Automatic 3D graph cuts for brain cortex segmentation in patients with focal cortical dysplasia

Ivana Despotovic UGent, Ief Segers, Ljiljana Platisa UGent, Ewout Vansteenkiste UGent, Aleksandra Pizurica UGent, Karel Deblaere UGent and Wilfried Philips UGent (2011) 2011 Annual international conference of the IEEE engineering in medicine and biology society (EMBC). p.7981-7984
abstract
In patients with intractable epilepsy, focal cortical dysplasia (FCD) is the most frequent malformation of cortical development. Identification of subtle FCD lesions using brain MRI scans is very often based on the cortical thickness measurement, where brain cortex segmentation is required as a preprocessing step. However, the accuracy of the selected segmentation method can highly affect the final FCD lesion detection. In this work, we propose an improved graph cuts algorithm integrating Markov random field-based energy function for more accurate brain cortex MRI segmentation. Our method uses three-label graph cuts and preforms automatic 3D MRI brain cortex segmentation integrating intensity and boundary information. The performance of the method is tested on both simulated MR brain images with different noise levels and real patients with FCD lesions. Experimental quantitative segmentation results showed that the proposed method is effective, robust to noise and achieves higher accuracy than other popular brain MRI segmentation methods. The qualitative validation, visually verified by a medical expert, showed that the FCD lesions were segmented well as a part of the cortex, indicating increased thickness and cortical deformation. The proposed technique can be successfully used in this, as well as in many other clinical applications.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
in
2011 Annual international conference of the IEEE engineering in medicine and biology society (EMBC)
pages
7981 - 7984
publisher
IEEE
place of publication
New York, NY, USA
conference name
33rd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBS)
conference location
Boston, MA, USA
conference start
2011-08-30
conference end
2011-09-03
Web of Science type
Proceedings Paper
Web of Science id
000298810006026
ISBN
9781424441228
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1842831
handle
http://hdl.handle.net/1854/LU-1842831
date created
2011-06-27 19:11:19
date last changed
2012-11-13 16:35:25
@inproceedings{1842831,
  abstract     = {In patients with intractable epilepsy, focal cortical dysplasia (FCD) is the most frequent malformation of cortical development. Identification of subtle FCD lesions using brain MRI scans is very often based on the cortical thickness measurement, where brain cortex segmentation is required as a preprocessing step. However, the accuracy of the selected segmentation method can highly affect the final FCD lesion detection. In this work, we propose an improved graph cuts algorithm integrating Markov random field-based energy function for more accurate brain cortex MRI segmentation. Our method uses three-label graph cuts and preforms automatic 3D MRI brain cortex segmentation integrating intensity and boundary information. The performance of the method is tested on both simulated MR brain images with different noise levels and real patients with FCD lesions. Experimental quantitative segmentation results showed that the proposed method is effective, robust to noise and achieves higher accuracy than other popular brain MRI segmentation methods. The qualitative validation, visually verified by a medical expert, showed that the FCD lesions were segmented well as a part of the cortex, indicating increased thickness and cortical deformation. The proposed technique can be successfully used in this, as well as in many other clinical applications.},
  author       = {Despotovic, Ivana and Segers, Ief and Platisa, Ljiljana and Vansteenkiste, Ewout and Pizurica, Aleksandra and Deblaere, Karel and Philips, Wilfried},
  booktitle    = {2011 Annual international conference of the IEEE engineering in medicine and biology society (EMBC)},
  isbn         = {9781424441228},
  language     = {eng},
  location     = {Boston, MA, USA},
  pages        = {7981--7984},
  publisher    = {IEEE},
  title        = {Automatic 3D graph cuts for brain cortex segmentation in patients with focal cortical dysplasia},
  year         = {2011},
}

Chicago
Despotovic, Ivana, Ief Segers, Ljiljana Platisa, Ewout Vansteenkiste, Aleksandra Pizurica, Karel Deblaere, and Wilfried Philips. 2011. “Automatic 3D Graph Cuts for Brain Cortex Segmentation in Patients with Focal Cortical Dysplasia.” In 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 7981–7984. New York, NY, USA: IEEE.
APA
Despotovic, I., Segers, I., Platisa, L., Vansteenkiste, E., Pizurica, A., Deblaere, K., & Philips, W. (2011). Automatic 3D graph cuts for brain cortex segmentation in patients with focal cortical dysplasia. 2011 Annual international conference of the IEEE engineering in medicine and biology society (EMBC) (pp. 7981–7984). Presented at the 33rd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBS), New York, NY, USA: IEEE.
Vancouver
1.
Despotovic I, Segers I, Platisa L, Vansteenkiste E, Pizurica A, Deblaere K, et al. Automatic 3D graph cuts for brain cortex segmentation in patients with focal cortical dysplasia. 2011 Annual international conference of the IEEE engineering in medicine and biology society (EMBC). New York, NY, USA: IEEE; 2011. p. 7981–4.
MLA
Despotovic, Ivana, Ief Segers, Ljiljana Platisa, et al. “Automatic 3D Graph Cuts for Brain Cortex Segmentation in Patients with Focal Cortical Dysplasia.” 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). New York, NY, USA: IEEE, 2011. 7981–7984. Print.