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Segmentation of brain parts from MRI image slices using genetic algorithm

Publication Type : Journal Article

Publisher : Lecture Notes in Computational Vision and Biomechanics

Source : Lecture Notes in Computational Vision and Biomechanics, Springer Netherlands, Volume 28, p.457-465 (2018)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042407650&doi=10.1007%2f978-3-319-71767-8_38&partnerID=40&md5=77624b16df9517fba6bfbd2a250c4684

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2018

Abstract : In this work a genetic algorithm based approach for segmenting the parts of brain MRI (Magnetic Resonance Imaging) image slices has been presented. Segmentation of the brain MRI image has been a challenging task and an open area for research off late due to reason that, the intensity differences between the different regions present in the image is very less. Hence a complete automation of segmentation process is difficult. In this work the various parameters of the genetic algorithm has been analyzed and an oprimized threshold value has been determined based on the slice type. The complexities in the segmentation algorithm and the challenges have also been reported. © 2018, Springer International Publishing AG.

Cite this Research Publication : K. Vikram, Menon, H. P., and Dhanya M. Dhanalakshmy, “Segmentation of brain parts from MRI image slices using genetic algorithm”, Lecture Notes in Computational Vision and Biomechanics, vol. 28, pp. 457-465, 2018.

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