Segmentation of Brain Regions Using Statistical Region Merging

Abstract

 Functional magnetic resonance imaging or functional MRI (FMRI) is a functional neuro imaging procedure using MRI technology that measures brain activity by detecting associated changes in blood flow, using blood– oxygen-level-dependent (BOLD) contrast. Current result from neuro science suggests modular organization of the brain. To understand, the complex interaction patterns among brain regions, existing system uses k-means (IKM) algorithm, an efficient algorithm for partitioning clustering. A cluster is defined as a set of subjects sharing a similar interaction pattern among their brain regions. IKM clusters only the particular regions or functions of the brain or rest of the nervous system. Hence it is not suitable for different regions of the time series. Hence the proposed Statistical Region Merging (SRM) algorithm is used for image segmentation. The algorithm is used to evaluate the values within a regional span and group them together based on the merging criteria resulting a smaller list and finally abnormality is detected.

Authors and Affiliations

Ms. P. Angalaparameswari*

Keywords

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  • EP ID EP153597
  • DOI -
  • Views 89
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How To Cite

Ms. P. Angalaparameswari* (30).  Segmentation of Brain Regions Using Statistical Region Merging. International Journal of Engineering Sciences & Research Technology, 3(2), 815-819. https://europub.co.uk/articles/-A-153597