Magnetic Resonance Imaging Research Paper

CERTAIN INVESTIGATION ON PATHOLOGIES IN

BRAIN IMAGES USING MRI SLICING

1Udayakumar. E, 2Roopasree.A,3Vetrivelan.P, 4Srihari.K

1PG Scholar-Communication Systems,Sri Ramakrishna Institute of Technology, Coimbatore.

2PG Scholar-Embedded System Technologies, Maharaja Institute of Technology, Coimbatore

3Associate Professor, Department of ECE, Sri Ramakrishna Institute of Technology, Coimbatore.

4Assistant Professor, Department of CSE, Sri Ramakrishna Institute of Technology, Coimbatore.

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Abstract--Medical imaging is used to diagnose or examine the diseases. Diagnostic technologies are usually responsible for acquiring medical images of diagnostic quality. Magnetic Resonance Imaging (MRI) is the imaging

When treating brain tumours, anatomical information to examine human brain development MRI imaging is often used. Magnetic Resonance Imaging provides detailed information about brain tumour anatomy, cellular structure and vascular supply, making it an important tool for the effective diagnosis, treatment and monitoring of the disease. The neurosurgical applications of MRI used to maximize tumour resection while avoiding damage to healthy brain tissue. There are various advantages of using digital images techniques like data is not changed when it is reproduced again and again and retains originality, enhancement of images makes work easier for physicians

Morphology provides a systematic approach to analyze the geometric characteristics of signals or images, and has been applied widely too many applications such as edge detection, objection segmentation, noise suppression and so on. Morphology aims to extend the binary morphological operators to grey-level images. Mathematical Morphology is a method for quantitative analysis of spatial structures that aims at analyzing shapes and forms of an object. Mathematical morphology is based on set theory. The shapes of objects in a binary image are represented by object membership sets. Objects are connected areas of pixels with value 1, the background pixels have value0.

Histogram Equalization:

The purpose of histogram equalization is to harmonize the image luminosity level distribution, in such a way that each of the histogram levels tend toward containing the same number of pixels. This operation aims at increasing the image nuanceHistogram equalization is a method in image processing of contrast adjustment using the image's histogram. This method usually increases the global contrast of many images.

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