Open AccessBrain Tumour Detection Using Machine Learning Algorithm
Author(s) -
A. Keerthana,
B. Kavin Kumar,
K.S Akshaya,
S. Kamalraj
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 - 10.1088/1742-6596/1937/1/012008
Subject(s) - cluster analysis , computer science , artificial intelligence , human brain , segmentation , identification (biology) , magnetic resonance imaging , feature extraction , feature (linguistics) , neuroimaging , machine learning , pattern recognition (psychology) , neuroscience , medicine , psychology , radiology , biology , linguistics , philosophy , botany
Brain is the regulatory unit in human body. It controls the functions such as memory, vision, hearing, knowledge, personality, problem solving, etc. The main reason for brain tumour is the abandoned progress of brain cells. Many health organizations have recognized brain tumour as the second foremost dispute that causes a large number of human deaths all around the world. Identification of brain tumour at a premature stage offers a opportunity of effective medical treatment. Use of Magnetic Resonance Imaging images have been recognized as more detailed and more consistent images when compared to Computed Tomography images. There are various techniques to detect brain tumour or neoplasms. The most competent and effective algorithms are discussed in this paper after studying a number of appropriate research papers. Pre-processing brain images, segmenting them, feature extraction, clustering and detection of the tumour are the methodologies in most researches.