Automatic ischemic stroke lesion segmentation using single MR modality and gravitational histogram optimization based brain segmentation

Nooshin Nabizadeh, Miroslav Kubat, Nigel John, Clinton Wright

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

3 Citations (Scopus)

Abstract

In this paper the automatic and customized brain segmentation followed by a stroke lesion detection technique is presented applying single modality Magnetic Resonance Images (MRIs). A novel intensity-based segmentation technique called gravitational histogram optimization is developed for this purpose. By applying histogram gravitational optimization algorithm the brain can be segmented into discriminative area including stroke lesion. The mathematical descriptions as well as the convergence criteria of the developed algorithm are presented in detail. The application of the proposed algorithm in the segmentation of single Diffusion-Weighted Images (DWI) modality of healthy and lesion MR image slices for different number of segments is presented and the results are discussed. The segmented areas are then employed in automatic lesion slice detection and lesion extraction technique. The stroke lesion is extracted from the recognized lesion slice with acceptable accuracy.

Original languageEnglish (US)
Title of host publicationProceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013
EditorsHamid R. Arabnia, Leonidas Deligiannidis, Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, Ashu M. G. Solo, Vladimir Volkov
PublisherCSREA Press
Pages207-213
Number of pages7
ISBN (Electronic)1601322526, 9781601322524
StatePublished - Jan 1 2013
Event2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013 - Las Vegas, United States
Duration: Jul 22 2013Jul 25 2013

Publication series

NameProceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013
Volume1

Conference

Conference2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013
CountryUnited States
CityLas Vegas
Period7/22/137/25/13

Fingerprint

Brain
Magnetic resonance

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

Cite this

Nabizadeh, N., Kubat, M., John, N., & Wright, C. (2013). Automatic ischemic stroke lesion segmentation using single MR modality and gravitational histogram optimization based brain segmentation. In H. R. Arabnia, L. Deligiannidis, J. Lu, F. G. Tinetti, J. You, G. Jandieri, G. Schaefer, A. M. G. Solo, ... V. Volkov (Eds.), Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013 (pp. 207-213). (Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013; Vol. 1). CSREA Press.

Automatic ischemic stroke lesion segmentation using single MR modality and gravitational histogram optimization based brain segmentation. / Nabizadeh, Nooshin; Kubat, Miroslav; John, Nigel; Wright, Clinton.

Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013. ed. / Hamid R. Arabnia; Leonidas Deligiannidis; Joan Lu; Fernando G. Tinetti; Jane You; George Jandieri; Gerald Schaefer; Ashu M. G. Solo; Vladimir Volkov. CSREA Press, 2013. p. 207-213 (Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013; Vol. 1).

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

Nabizadeh, N, Kubat, M, John, N & Wright, C 2013, Automatic ischemic stroke lesion segmentation using single MR modality and gravitational histogram optimization based brain segmentation. in HR Arabnia, L Deligiannidis, J Lu, FG Tinetti, J You, G Jandieri, G Schaefer, AMG Solo & V Volkov (eds), Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013. Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, vol. 1, CSREA Press, pp. 207-213, 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013, Las Vegas, United States, 7/22/13.
Nabizadeh N, Kubat M, John N, Wright C. Automatic ischemic stroke lesion segmentation using single MR modality and gravitational histogram optimization based brain segmentation. In Arabnia HR, Deligiannidis L, Lu J, Tinetti FG, You J, Jandieri G, Schaefer G, Solo AMG, Volkov V, editors, Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013. CSREA Press. 2013. p. 207-213. (Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013).
Nabizadeh, Nooshin ; Kubat, Miroslav ; John, Nigel ; Wright, Clinton. / Automatic ischemic stroke lesion segmentation using single MR modality and gravitational histogram optimization based brain segmentation. Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013. editor / Hamid R. Arabnia ; Leonidas Deligiannidis ; Joan Lu ; Fernando G. Tinetti ; Jane You ; George Jandieri ; Gerald Schaefer ; Ashu M. G. Solo ; Vladimir Volkov. CSREA Press, 2013. pp. 207-213 (Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013).
@inproceedings{bc2b4a1b9e4f412f93952c2d1a2f428e,
title = "Automatic ischemic stroke lesion segmentation using single MR modality and gravitational histogram optimization based brain segmentation",
abstract = "In this paper the automatic and customized brain segmentation followed by a stroke lesion detection technique is presented applying single modality Magnetic Resonance Images (MRIs). A novel intensity-based segmentation technique called gravitational histogram optimization is developed for this purpose. By applying histogram gravitational optimization algorithm the brain can be segmented into discriminative area including stroke lesion. The mathematical descriptions as well as the convergence criteria of the developed algorithm are presented in detail. The application of the proposed algorithm in the segmentation of single Diffusion-Weighted Images (DWI) modality of healthy and lesion MR image slices for different number of segments is presented and the results are discussed. The segmented areas are then employed in automatic lesion slice detection and lesion extraction technique. The stroke lesion is extracted from the recognized lesion slice with acceptable accuracy.",
author = "Nooshin Nabizadeh and Miroslav Kubat and Nigel John and Clinton Wright",
year = "2013",
month = "1",
day = "1",
language = "English (US)",
series = "Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013",
publisher = "CSREA Press",
pages = "207--213",
editor = "Arabnia, {Hamid R.} and Leonidas Deligiannidis and Joan Lu and Tinetti, {Fernando G.} and Jane You and George Jandieri and Gerald Schaefer and Solo, {Ashu M. G.} and Vladimir Volkov",
booktitle = "Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013",

}

TY - GEN

T1 - Automatic ischemic stroke lesion segmentation using single MR modality and gravitational histogram optimization based brain segmentation

AU - Nabizadeh, Nooshin

AU - Kubat, Miroslav

AU - John, Nigel

AU - Wright, Clinton

PY - 2013/1/1

Y1 - 2013/1/1

N2 - In this paper the automatic and customized brain segmentation followed by a stroke lesion detection technique is presented applying single modality Magnetic Resonance Images (MRIs). A novel intensity-based segmentation technique called gravitational histogram optimization is developed for this purpose. By applying histogram gravitational optimization algorithm the brain can be segmented into discriminative area including stroke lesion. The mathematical descriptions as well as the convergence criteria of the developed algorithm are presented in detail. The application of the proposed algorithm in the segmentation of single Diffusion-Weighted Images (DWI) modality of healthy and lesion MR image slices for different number of segments is presented and the results are discussed. The segmented areas are then employed in automatic lesion slice detection and lesion extraction technique. The stroke lesion is extracted from the recognized lesion slice with acceptable accuracy.

AB - In this paper the automatic and customized brain segmentation followed by a stroke lesion detection technique is presented applying single modality Magnetic Resonance Images (MRIs). A novel intensity-based segmentation technique called gravitational histogram optimization is developed for this purpose. By applying histogram gravitational optimization algorithm the brain can be segmented into discriminative area including stroke lesion. The mathematical descriptions as well as the convergence criteria of the developed algorithm are presented in detail. The application of the proposed algorithm in the segmentation of single Diffusion-Weighted Images (DWI) modality of healthy and lesion MR image slices for different number of segments is presented and the results are discussed. The segmented areas are then employed in automatic lesion slice detection and lesion extraction technique. The stroke lesion is extracted from the recognized lesion slice with acceptable accuracy.

UR - http://www.scopus.com/inward/record.url?scp=85000655974&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85000655974&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85000655974

T3 - Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013

SP - 207

EP - 213

BT - Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013

A2 - Arabnia, Hamid R.

A2 - Deligiannidis, Leonidas

A2 - Lu, Joan

A2 - Tinetti, Fernando G.

A2 - You, Jane

A2 - Jandieri, George

A2 - Schaefer, Gerald

A2 - Solo, Ashu M. G.

A2 - Volkov, Vladimir

PB - CSREA Press

ER -