Lung Cancer Detection from X-ray images by combined Backpropagation Neural Network and PCA

Abed, Israa S.

doi:10.30684/etj.37.5A.3

	Lung Cancer Detection from X-ray images by combined Backpropagation Neural Network and PCA
Engineering and Technology Journal
Article 3, Volume 37, 5A, 2019, Pages 166-171 PDF (956.03 K)
Document Type: Research Paper
DOI: 10.30684/etj.37.5A.3
Author
Israa S. Abed
Biomedical Engineering Department, Al-Khwarizmi College of Engineering, University of Baghdad
Abstract
The lungs are portion of a complex unit, enlarging and relaxing numerus times every day to supply oxygen and exude CO2. Lung disease might occur from troubles in any part of it. Carcinoma often called Cancer is the generally rising and it is the most harmful disease happened in humankind. Carcinoma occurs because of uncontrolled growth of malignant cells inside the tissues of the lungs. Earlier diagnosis of cancer can help save large numbers of lives, while any delay or fail in detection may cause additional serious problems leading to sudden fatal death. The objective of this study is to design an automated system with an ability to improve the detection process in order to perform advanced recognition of the disease. The diagnosis techniques include: X-rays, MRI, CT images etc. X-ray is the common and low-cost technique that is widely used and it is relatively available for everyone. Rather than new techniques like CT and MRI, X-ray is human dependable, meaning it needs a Doctor and X-ray specialist in order to determine lung cases, so developing a system which can enhance and aid in diagnosis, can help specialist to determine cases in easily.
Keywords
Lung Cancer; Intelligent Systems; Classification; feature extraction; Pattern Recognition

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