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ABSTRACT:
The part of the image that has the tumor has more intensity in that portion and we can make our assumptions about the radius of the tumor in the image,these are the basic things considered in the algorithm.First of all some image enhancement and noise reduction techniques are used to enhance the image quality,after that some morphological operations are applied to detect the tumor in the image.The morphological operations are basically applied on some assumptions about the size and shape of the tumor and ....etc

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Brain tumor detection from MRI
A Project Report
Submitted in partial fulfilment of
the requirements for the award of the degree of
Master of Technology
in
Computer Science and Engineering
by
Irene Antony Tharayil
M105107
Department of Computer Science & Engineering
College of Engineering Trivandrum
Kerala - 695016
2010-11

Abstract
Brain tumor is one of the major causes for the increase in mortality among children and
adults.A tumor is a mass ....etc

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AIM AND KEY WORDS OF THIS TOPIC IS to detect the exact location of tumor without disturbing the entire image.

(E)EDGE PARAMETER(EDGE DETECTION)
(G)GRAY PARAMETER
(H)LOCAL CONTRAST, WATERSHED SEGMENTATION.

**BLOCK DIAGRAM IS AS SHOWN BELOW: **

MRI image as input --> preprocessing --> division into blocks -->
--> E --> G --> H --> watershed segmentation --> 2D visiualization

so far i tried like this..

firstly i have read an brain tumor mri image,by using 'imtool' command observed the pixels values. now as already we are ....etc

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Biometrics (or biometric authentication) refers to the process of identification of humans by their characteristics or traits. Biometrics is used in computer science as a form of identification and access control which is one of the most secure methods to keep humans privacy. Biometric can be classified into two categories: behavioural (signature verification, keystroke dynamics, etc.) and physiological (iris characteristics, fingerprint, etc.). Handwritten signature is amongst the first few biometrics to be used even before the advent of compu ....etc

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matlab code for brain tumour extraction from mri images

ABSTRACT
Medical imaging is generally equated to radiology or clinical imaging and the medical practitioner responsible for interpreting (and sometimes acquiring) the image is a radiologist. Diagnostic radiography designates the technical aspects of medical imaging and in particular the acquisition of medical images. The radiographer or radiologic technologist is usually responsible for acquiring medical images of diagnostic quality, although some radiological interventions are performe ....etc

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Brain Tumor detection using Color-Based K-means Clustering Segmentation

INTRODUCTION

This paper proposes a color-based segmentation method that uses the K-means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color-based segmentation algorithm with K-means is to convert a given gray-level MR image into a color space image and then separate th ....etc

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There are over 100 different types of brain tumours. They are commonly named after the type of cell they come from. Most brain tumours develop from glial cells, which grow from the supporting cells of the brain. These tumours are called gliomas . Tumours that begin in the brain are known as primary brain tumours.
Some types of brain tumours are malignant (cancerous) and others are benign (non-cancerous). Differences include:
Benign brain tumours are often slow growing and are unlikely to spread, but they can press on and damage the surrou ....etc

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Pls post me a detailed report on detection of brain tumour using image processing techniques. ....etc

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pls i need literature review on brain tumor detection using color based k means clustering segmentation for my project
need literature review on brain tumor detection using color based k means clustering segmentation urgently
literature review on brain tumor detection using color based k means clustering segmentation ....etc

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