AN SURVERY ON LUNG CANCER DISEASES DETECTION (LCDD) USING IMAGE MINING APPROACHES AMONG NON- SMOKERS
Author(s):
B.MOHAMED FAIZE BASHA, Dr.M.MOHAMED SURPUTHEEN
Keywords:
image mining, cancer, cell, tumours, smokers
Abstract
This paper proposed a method for detection or identifying lung cancer diseases affect and curing possibilities, especially non-smokers. The factors impact approaches are drivers, formers, kids, women and others... Image mining is primarily used to the requirements of finding the various applications in diverse fields such as retail, financial, communication, marketing organizations and medicine, For Improve the detection of disease in the medical field image mining techniques is widely used today. It may recover possible to the early stage. In general lung cancer is the uncontrolled growth of abnormal cells that start off in one or both lungs. The cancer cells can break and damage the tissues and also organs near the tumours of the body. It spread from one place to another. Using image quality and accuracy is the main factor for earlier disease detection and treatment stages including non-smokers also. Image mining has two different approaches one is extracted and collected in pattern. It is necessary to combine the different image formats to a regular format. In Feature Extraction, classification, image mining provides the framework for further improvement in other type of cancers in medical field. We planned to the associative classification methodology to detect particularly lungs affects and curing possibilities.
Article Details
Unique Paper ID: 143858

Publication Volume & Issue: Volume 3, Issue 3

Page(s): 4 - 7
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Last Date 25 March 2018


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