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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)

International Peer Reviewed & Refereed Journals, Open Access Journal

IJCRT Peer-Reviewed (Refereed) Journal as Per New UGC Rules.

ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013

Call For Paper - Volume 14 | Issue 8 | Month- August 2026

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  Published Paper Details:

  Paper Title

AUTOMATIC BRAIN TUMOUR SEGMENTATION USING PROBABILISTIC NEURAL NETWORK AND GAUSSIAN MIXTURE MODEL

  Authors

  J.Anandhi ,  K.Asvini,  R.Aswitha,  R.Dhanushia,  R.Jeevitha, Sherlin Suresh

  Keywords

Segmentation of the growing mind is wanted for the take a look at of regular fetal mind improvement and neurodevelopmental problems. Manual segmentation of thoughts MRI facts is time-eating, tedious and subjective. Previously, a extensive variety of methodologies has been proposed for computerized segmentation of the mature thoughts. Compared to man or woman snapshots, MRI time series brings a numerous facts. This statistics permits scientific docs to discover tumor in human thoughts. Medical im

  Abstract


Segmentation of the growing mind is wanted for the take a look at of regular fetal mind improvement and neurodevelopmental problems. Manual segmentation of thoughts MRI facts is time-eating, tedious and subjective. Previously, a extensive variety of methodologies has been proposed for computerized segmentation of the mature thoughts. Compared to man or woman snapshots, MRI time series brings a numerous facts. This statistics permits scientific docs to discover tumor in human thoughts. Medical imagery can be very sensitivity as it is related to human health. Actually, tumor localization in human mind is a delicate mission. Therefore, the use of a multi temporal collection of MRI images permits a better extraction due to the additional statistics delivered with the aid of way of every picture in the time collection. Compared to individual pics, MRI time collection brings a various data. This data lets in docs to locate tumor in human mind. Medical imagery may be very sensitivity as it is associated with human health. Actually, tumor localization in human mind is a touchy mission. Therefore, the usage of a multi temporal collection of MRI snap shots permits a better extraction due to the extra information introduced via every photograph within the time collection.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT1801644

  Paper ID - 185042

  Page Number(s) - 798-805

  Pubished in - Volume 6 | Issue 1 | March 2018

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  J.Anandhi ,  K.Asvini,  R.Aswitha,  R.Dhanushia,  R.Jeevitha, Sherlin Suresh,   "AUTOMATIC BRAIN TUMOUR SEGMENTATION USING PROBABILISTIC NEURAL NETWORK AND GAUSSIAN MIXTURE MODEL", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.6, Issue 1, pp.798-805, March 2018, Available at :http://www.ijcrt.org/papers/IJCRT1801644.pdf

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Call For Paper August 2026
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
ISSN
ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
ISSN
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