@inproceedings{fc327019e1884ef2a8629d97c8bdd32a,
title = "Design and implementation of a computer-aided diagnosis system for brain tumor classification",
abstract = "Computer-aided diagnosis (CAD) systems have become very important for the medical diagnosis of brain tumors. The systems improve the diagnostic accuracy and reduce the required time. In this paper, a two-stage CAD system has been developed for automatic detection and classification of brain tumor through magnetic resonance images (MRIs). In the first stage, the system classifies brain tumor MRI into normal and abnormal images. In the second stage, the type of tumor is classified as benign (Noncancerous) or malignant (Cancerous) from the abnormal MRIs. The proposed CAD ensembles the following computational methods: MRI image segmentation by K-means clustering, feature extraction using discrete wavelet transform (DWT), feature reduction by applying principal component analysis (PCA). The two-stage classification has been conducted using a support vector machine (SVM). Performance evaluation of the proposed CAD has achieved promising results using a non-standard MRIs database.",
keywords = "benign tumor, Brain tumor, DWT, K-means, malignant tumor, MRIs, PCA, SVM, tumor classification, tumor detection",
author = "Abd-Ellah, {Mahmoud Khaled} and Awad, {Ali Ismail} and Khalaf, {Ashraf A.M.} and Hamed, {Hesham F.A.}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 28th International Conference on Microelectronics, ICM 2016 ; Conference date: 17-12-2016 Through 20-12-2016",
year = "2016",
month = jul,
day = "2",
doi = "10.1109/ICM.2016.7847911",
language = "English",
series = "Proceedings of the International Conference on Microelectronics, ICM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "73--76",
booktitle = "ICM 2016 - 28th International Conference on Microelectronics",
address = "United States",
}
