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MRI Image Brain Tumor Detection and Segmentation Using Texture-based Statistical Characterization Method


P. Ratha, Dr.B. Mukundan and Dr.G. Rakesh
Abstract

As it was observed earlier, segmentation is ace of the central challenges in car learning and computing machine imagination realm. In medical diagnostics field, brain tumor segmentation is a significant and demanded application, as it allows for medical experts the data associated to wounds, which assistants to control and decrease the effects of the illness. There are intensity resemblances amongst brain wounds and almost pattern weaves that can answer in confusedness between the algorithms. T1-weighted MR image, and tumor lesion accepts like intensities to those of GM or CSF Owing to this fact; universal image segmentation methods constitute not well relevant along the brain lesion credit area. In order to defeat intensity similarities trouble, one general answer is using multi-spectral MR images since lesion recognition. However, as it was noted in the first place applying multi-spectral MR images have its own limitations and troubles. Since of these impediments, brain lesion detection and segmentation expending individual -spectral anatomical MR image exists desirable.

Volume 12 | 04-Special Issue

Pages: 595-609

DOI: 10.5373/JARDCS/V12SP4/20201526