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 imag ....etc

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what is the means of rajasthan univetsity result efps in marksheet ....etc

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ABSTRACT
Breast cancer is one of the major causes of death among women.
Small clusters of micro calcifications appearing as collection of
white spots on mammograms show an early warning of breast
cancer. Early detection performed on X-ray mammography is the
key to improve breast cancer diagnosis. In order to increase
radiologist’s diagnostic performance, several computer-aided
diagnosis (CAD) schemes have been developed to improve the
detection of primary identification of this disease. In this paper, an
attempt is made to de ....etc

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Abstract

The accuracy of the precise machines (e.g. Coordinate measuring machines) is of micrometer range and even less. The play of the bearings, the change of the position of moving parts, wear, environment influence, etc. reduce the final accuracy. The existing methods to increase the accuracy of precise equipment are complicated and of high cost. The authors present a new concept in the design of error compensating systems - active frames and structures for precision technological equipment and measuring machines. It is proposed to inser ....etc

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PRESENTED BY:
Narmadha.K
Panimalar.R
Pavithra.P
Praveena.M


FLEXIBLE HARDWARE ARCHITECTURE OF HIERARCHICAL K-MEANS CLUSTERING FOR LARGE CLUSTER NUMBER

ABSTRACT
 To Handle Large Cluster Number In Embedded Systems, A Hardware Architecture Of Hierarchical K-means (Hk-means) Is Proposed To Support A Maximum Cluster Number Of 1024.
 It Adopts 10 Processing Elements For The Euclidean Distance Computations And The Level-order Binary-tree Traversal
 The Gate Count Of The Hardware Is 4 ....etc

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N i think i am having back 1 back in 2 nd year did i get the next chance for clear it.. ....etc

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ABSTRACT

Template matching is an object detection technique in image processing to find small parts of an image which match a template image. There are many methods one can adopt for this purpose.

Matching can be Template based, in which case every pixel that contributes to the template may be matched against every pixel of the image using any means of comparison (eg. SAD, SSD, cross-correlation), or it can me Feature based, where the matching is on the basis of some strong features that the template ma ....etc

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Abstract
A non-destructive estimation of the state-of-charge _SoC. of batteries facilitates optimum utilization of the battery for a given application, as well as evaluation of its state-of-health. Among various methods, a.c. impedance spectroscopy over a wide range of frequencies provides a variety of parameters which are functions of the SoC of a given battery. These parameters and their variation with SoC depend on the type of battery and on the experimental conditions. The impedance data of sealed commercial cells are rather tedious to a ....etc

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Myself BLACK,doing my Engineering final year in PSP college.For my final year project i am working Medical image processing field.Now i want ideas regarding the article Non local means speckle filtering of ultrasound images using Bayesian framework.I have attached the abstract of the project.

Abstract”In image processing, restoration is expected to improve
the qualitative inspection of the image and the performance
of quantitative image analysis techniques. In this paper, an adaptation
of the nonlocal (NL)-means filter is propos ....etc

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I am doing a project on realization of clustering using k-means algorithm.

Can any one help me to realize the following matlab codes,how it works,specifications and detail explanations regarding the code functions and its implementations, please help me out.


1.
function d=DistMatrix(A,B)
=size(A);
=size(B);
if hA==1& hB==1
d=sqrt(dot((A-B),(A-B)));
else
C=;
D=flipud(C);
E=;
F=flipud(E);
G=A*C;
H=A*D;
I=B*E;
J=B*F;
d=sqrt((G-I').^2 ....etc

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