Open AccessAutomatic clustering based approach for brain tumor extraction
Author(s) -
Akshya Kumar Sahoo,
Priyadarsan Parida
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1921/1/012007
Subject(s) - white matter , brain cancer , cluster analysis , brain tumor , computer science , brain tissue , skull , population , extraction (chemistry) , stage (stratigraphy) , artificial intelligence , pattern recognition (psychology) , cancer , pathology , neuroscience , medicine , radiology , biology , magnetic resonance imaging , anatomy , chemistry , chromatography , paleontology , environmental health
The brain cancer is a deadly disease affecting almost 1.7% of world’s population with top mortality rate. The basic cause of brain cancer is the abnormal growth of brain tissues in the early stage. Further, these tissues are converted into tumors. Early detection and exact location of brain tumor can assist for further therapies of brain. In this paper a computer vision-based approach is developed for exacting an exact location of the brain tumors from the MRI images. The method starts from skull stripping for removal of the outer portion of brain and segregate the white matter. Further communication with local agent (CLA) clustering technique is applied followed by morphological post processing methods for extraction of tumor regions from white matter regions of the brain. The method is tested on a publicly available MRI dataset. Quantitative and qualitative measures show that the proposed method achieves an accuracy of 99.64% as compared to others.