Lung Cancer Detection Model Using Convolution Neural Network and Fuzzy Clustering Algorithms
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2019 by IJCTT Journal|
|Year of Publication : 2019|
|Authors : P. Prakashbabu, D. Ashok Kumar, T.Vithyaa|
|DOI : 10.14445/22312803/IJCTT-V67I11P104|
MLA Style:P. Prakashbabu, D. Ashok Kumar, T.Vithyaa "Lung Cancer Detection Model Using Convolution Neural Network and Fuzzy Clustering Algorithms," International Journal of Computer Trends and Technology 67.11 (2019):18-27.
APA Style P. Prakashbabu, D. Ashok Kumar, T.Vithyaa. Lung Cancer Detection Model Using Convolution Neural Network and Fuzzy Clustering Algorithms International Journal of Computer Trends and Technology, 67(11),18-27.
This paper discusses the formation of Lung cancer detection system by using the techniques of Image processing. The system formed can take any type of medical image within the three choices consisting of CT, MRI and Ultrasound images. Here the proposed model is developed using Fuzzy-CMeans and Convolution Neural Network (CNN) algorithm used for feature selection. This paper is an extension of image processing using lung cancer detection and produces the results of feature extraction and feature selection after segmentation. The system formed accepts any one of medical image within the three choices consisting of MRI, CT and Ultrasound image as input. After preprocessing of image, wiener filter is used for remove noise and unwanted region. This present work proposes a method to detect the cancerous cells effectively from the CT, MRI scan and Ultrasound images. Pixel Segmentation has been used for FCM segmentation and filter is used for De-noising the medical images. Simulation results are obtained for the cancer detection system using MATLAB and comparison is done between normal lung and abnormallung medical images.
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Lung cancer,lung segmentation,Fuzzy-CMeans, CNN, Feature extraction.