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Content Based Image Retrieval (CBIR) System for Diagnosis of Blood Related Diseases

Published on December 2013 by Jignyasa Sanghavi, Deepali Kayande
National Conference on Innovative Paradigms in Engineering & Technology 2013
Foundation of Computer Science USA
NCIPET2013 - Number 1
December 2013
Authors: Jignyasa Sanghavi, Deepali Kayande
63653480-b3f4-4e4f-b776-e10fe78231ba

Jignyasa Sanghavi, Deepali Kayande . Content Based Image Retrieval (CBIR) System for Diagnosis of Blood Related Diseases. National Conference on Innovative Paradigms in Engineering & Technology 2013. NCIPET2013, 1 (December 2013), 11-15.

@article{
author = { Jignyasa Sanghavi, Deepali Kayande },
title = { Content Based Image Retrieval (CBIR) System for Diagnosis of Blood Related Diseases },
journal = { National Conference on Innovative Paradigms in Engineering & Technology 2013 },
issue_date = { December 2013 },
volume = { NCIPET2013 },
number = { 1 },
month = { December },
year = { 2013 },
issn = 0975-8887,
pages = { 11-15 },
numpages = 5,
url = { /proceedings/ncipet2013/number1/14694-1306/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Innovative Paradigms in Engineering & Technology 2013
%A Jignyasa Sanghavi
%A Deepali Kayande
%T Content Based Image Retrieval (CBIR) System for Diagnosis of Blood Related Diseases
%J National Conference on Innovative Paradigms in Engineering & Technology 2013
%@ 0975-8887
%V NCIPET2013
%N 1
%P 11-15
%D 2013
%I International Journal of Computer Applications
Abstract

The identification of the disease is very crucial step for curing disease. In many cases microscopic analysis of peripheral blood samples by medical practitioner is an important test in the procedures for the diagnosis of any blood related disease. Accurate diagnosis of disease is crucial for curing and controlling that disease. Earlier this process was carried out only by medical experts but now a day's automated system based on computer vision methods or image processing algorithms can speed up this operation. The expert systems are developed which are doing computerized diagnosis of various diseases using digital images of blood samples. Digital images are acquired using a digital camera connected to microscope. The presented paper shows the automatic diagnosis for three diseases i. e. Leukemia, Malaria and Sickle cell Anaemia. The system firstly segments the infected cells of leukemia and sickle cell anaemia or parasites of malaria from the blood samples and extracts the features of these cells or parasites. These features are then compared with database and accordingly classification is done and is represented in CBIR (Content Based Image Retrieval) framework.

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Index Terms

Computer Science
Information Sciences

Keywords

Malaria Leukemia Sickle Cell Anaemia Expert System Cbir (content Based Image Retrieval) Framework Automated System Computerized Diagnosis.