文章基本信息

标题：Survey on Brain Tumor Detection using K-Means Clustering Algorithm
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作者：Prof. B.R. Quazi ; Supriya Mali ; Smita More 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：1
页码：1001
DOI：10.15680/IJIRCCE.2017.0501048
出版社：S&S Publications
摘要：This paper deals with the survey of simple algorithm that detects tumor area and its accurate size inbrain MR images. Brain tumor is inherently serious and life-threatening because of its character in the limited space ofthe intra-cranial cavity. Most Research in developed countries show that the number of people who have braintumorswere died due to the fact of inaccurate detection. Generally, CT scan or MRI that is directed into intra-cranialcavity produces a complete image of brain. This image is visually examined by the physician for detection anddiagnosis of brain tumor. However this method defy the accurate determination of stage. To avoid that, this project usescomputer aided method for detection of brain tumor based on K-means algorithm. This method allows thesegmentation of tumor tissue with accuracy and reproducibility comparable to manual segmentation. In addition, it alsoreduces the time for analysis. At the end of the process the tumor is extracted from the Magnetic Resonance Image andits exact position and the shape is also determined. The stage of the tumor is displayed based on the amount of areacalculated from the cluster. In addition with image processing we are using Hadoop for storing segmented MRI Images
关键词：K-means Clustering; Magnetic Resonance Imaging(MRI); Thresholding; Brain Tumor analysis;Hadoop