Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach
Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3669170Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 462
 Yang Chunran, Wang Yuanyuan and Guo Yi, “Automatic Detection and Segmentation of Lung Nodule on CT Images”- 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI 2018) –2018, IEEE.
 Ahmed Shaffie, Ahmed Soliman, Hadil Abu Khalifeh, Mohammed Ghazal, Fatma Taher, Robert Keynton, Adel Elmaghraby and Ayman El-baz, “On The Integration of CT-Derived Features for Accurate Detection of Lung Cancer” – 978-1-5386-7568-7/18/$31.00 – 2018, IEEE.
 Chen Zhao, Jungang Han, Yang Jia and Fan Gou, “Lung Nodule Detection via 3D U-Net and Contextual Convolutional Neural Network”–2018 International Conference on Networking and Network Applications, IEEE.
 Bariqi Abdillah, Alhadi Bustamam, and Devvi Sarwinda, “Image processing based detection of lung cancer on CT scan images” – The Asian Mathematical Conference 2016 (AMC 2016) - IOP Conf. Series: Journal of Physics: Conf. Series 893 (2017) 012063.
 Achim Cristian, Rusu-Both Roxana, Dulf Eva-Henrietta and Chira Romeo Ioan, “Lung Cancer Diagnosis based on Ultrasound image processing” – 22nd International Conference on System Theory, Control and Computing (ICSTCC)- IEEE, 2018.
 Bohdan Chapaliuk and Yuriy Zaychenko, “Deep Learning Approach in Computer-Aided Detection System for Lung Cancer” – 978-1-5386-7196-2/18/$31.00, 2018, IEEE.
 Diptarup Bhattacharya, Pradeep Kumar Rathore and Shubhankar Majumdar, “Non-Invasive Piezoelectric Sensor for Detection of Lung Cancer” - International Conference on Communication and Electronics Systems (ICCES 2018) - IEEE 2018.
 Pooja R. Katre and Dr. Anuradha Thakare, “Detection of Lung Cancer Stages using Image Processing and Data Classification Techniques”, 2nd International Conference for Convergence in Technology (I2CT) – IEEE 2017.
 Gawade Prathamesh Pratap and R.P. Chauhan, “Detection of Lung Cancer Cells using Image Processing Techniques”- 1st IEEE International Conference on Power Electronics. Intelligent Control and Energy Systems (ICPEICES-2016) - IEEE 2016.
 De-Ming Wong, Chen-Yu Fang, Li-Ying Chen, Chen-I Chiu, Ting-I Chou, Cheng-Chun Wu, Shih-Wen Chiu and Kea-Tiong Tang, “Development of a Breath Detection Method Based E-nose System for Lung Cancer Identification” – IEEE International Conference on Applied System Innovation 2018 – IEEE ICASI 2018.
 Kelly M. Latimer, Md, Mph and Timothy F. Mott, Md, Naval Hospital Pensacola, Pensacola, Florida -“Lung Cancer: Diagnosis, Treatment Principles, and Screening”- Medical Journal–American family Physician website - www.aafp.org/afp -2015.
 Ajay Aggarwal, Grant Lewison, Saliha Idir, Matthew Peters, Carolyn Aldige, Win Boerckel, Peter Boyle, Edward L. Trimble, Philip Roe,Tariq Sethi, Jesme Fox, Richard Sullivan, - “The State of Lung Cancer Research: A Global Analysis”- 2016, International Association for the Study of Lung Cancer - Journal of Thoracic Oncology Vol. 11 No. 7: 1040-1050 – 2016, http://creativecommons.org/licenses/by-nc-nd/4.0/