@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 Wright, {Clinton B}",
year = "2013",
month = jan,
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",
note = "2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013 ; Conference date: 22-07-2013 Through 25-07-2013",
}