REVIEWON COMPUTER AIDED DIAGONOSTIC SYSTEM FOR DETECTION OF LUNG CANCER BY USING IMAGE PROCESSING
Author(s):
Ashwini Dattatraya Gopwad, Reshma Ramadas Nitnaware, Dr. Ajit Maslekar
Keywords:
Abstract
Identification of lung cancer is an effective way to minimize the death rate and maximize survival rate of cases. It is an essential step to screen out the reckoned tomography (CT) images for pulmonary nodes towards the effective treatment of lung cancer. still, robust bump identification and discovery is a most critical task due the complexity of the girding terrain and diversity of the lung nodes. The use of machine literacy to descry, prognosticate, and classify complaint has grown exponentially in the once many times, especially for complex tasks similar as lung cancer discovery and recognition. Deep Convolutional neural networks (DCNN) have exploded in fashion ability for transubstantiating the field of computer vision exploration. In this paper, we're using Deep Convolutional Neural Network for lung cancer bracket using CT images grounded lung cancer image dataset institute (LIDC) for detecting cancerous and noncancerous lung nodes for measuring the delicacy of bracket better than being styles.
Article Details
Unique Paper ID: 158167

Publication Volume & Issue: Volume 9, Issue 9

Page(s): 10 - 13
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