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Brain Tumor Detection Using MRI Images
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Abstract: Most cells in the body grow and then divide in an orderly way to form new cells as they are needed to keep the body healthy and working properly. When cells lose the ability to control their growth, they divide too often and without any order. The extra cells form a mass of tissue called a tumor. Brain tumors are abnormal and uncontrolled proliferations of cells. Segmentation methods used in biomedical image processing and explores the methods useful for better segmentation. A critical appraisal of the current status of semi automated and automated methods are made for the segmentation of anatomical medical images emphasizing the advantages and disadvantages. In this project we detect the brain tumor & classify the stages of the tumor by using testing & training the database. Segmentation for testing purpose is done by spatial FCM used.
Keywords: Brain MR, image segmentation, learning vector quantization, self-organizing feature map, stationary wavelet transform.
Keywords: Brain MR, image segmentation, learning vector quantization, self-organizing feature map, stationary wavelet transform.
How to Cite:
[1] Pranita Balaji Kanade, Prof. P.P. Gumaste, βBrain Tumor Detection Using MRI Images,β International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI: 10.17148/IJIREEICE.2015.3231
