Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3370
Title: ANDROID APPLICATIONS FOR LUNG NODULES CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK
Authors: Karthikeyan, M P
Banupriya, C V
Kowsalya, R
Jayalakshmi, A
Issue Date: 2023
Publisher: IGI Global
Abstract: Digital image processing is currently used in various fields of research. One of them is in the field of medicine. In fact, experienced radiologists have difficulty distinguishing the cancerous portions of the blood vessels in the lung or detecting fine nodules that suggest lung cancer on X-ray images. Previous studies have shown that doctors and radiologists fail to detect cancerous patches in 30% of positive cases. Implementation of CAD system to classify and detect parts of cancer has been developed, but the results obtained from this implementation are that there are still many errors in the classification results. Therefore, this study will develop android app image technique to perform the classification process of lung cancer. With this research, it is hoped that the developed algorithm can help doctors and radiologists to detect cancer in a short time with more accuracy. Finally, after 20 iterations, a percentage of 90.65% was attained for the test results' performance in classifying 10 X-ray pictures.
URI: https://www.igi-global.com/chapter/android-applications-for-lung-nodules-classification-using-convolutional-neural-network/322071
Appears in Collections:International Journals

Files in This Item:
File Description SizeFormat 
ANDROID APPLICATIONS FOR LUNG NODULES CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK.docx214.92 kBMicrosoft Word XMLView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.