Identification of Cancer Disease Using Image Processing Approahes
International Journal of Intelligent Information Systems
Volume 9, Issue 2, April 2020, Pages: 6-15
Received: May 14, 2020; Accepted: Jun. 2, 2020; Published: Jul. 4, 2020
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Authors
Saif Ali, University Institute of Information Technology, PMAS Arid Agriculture University, Rawalpindi, Pakistan
Aneeqa Tanveer, University Institute of Information Technology, PMAS Arid Agriculture University, Rawalpindi, Pakistan
Azhar Hussain, University Institute of Information Technology, PMAS Arid Agriculture University, Rawalpindi, Pakistan
Saif Ur Rehman, University Institute of Information Technology, PMAS Arid Agriculture University, Rawalpindi, Pakistan
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Abstract
Cancer, also called malignancy, is an abnormal growth of cells. There are more than 100 types of cancer, including breast cancer, skin cancer, lung cancer, colon cancer, prostate cancer, and lymphoma. Symptoms vary depending on the type. Cancer treatment may include chemotherapy, radiation, and/or surgery. According to American Cancer Society America will be encountering 1,806,950 new cases of cancer in the year 2020 causing 606,520 deaths. Cancer is the leading cause of death in the world. Cancer can be classified into two main categories malignant and benign. Early detection of cancer is the key to the successful treatment of cancer. There are various methodologies for the detection of cancer some include manual procedures, Manual identification is time-consuming and unreliable therefore computer-aided detection came into the research. Computer-aided detection involves image processing for feature extraction and classification techniques for the recognition of cancer type and stages. In this paper, several different algorithms have been discussed such as SVM, KNN, DT, etc. for the classification of the different cancers. This paper also presents a comparative analysis of the researches done in the past.
Keywords
Image Processing, Acute Lymphoblastic Leukemia, ALL, Blood Cancer, Image Segmentation, Performance, Efficiency
To cite this article
Saif Ali, Aneeqa Tanveer, Azhar Hussain, Saif Ur Rehman, Identification of Cancer Disease Using Image Processing Approahes, International Journal of Intelligent Information Systems. Vol. 9, No. 2, 2020, pp. 6-15. doi: 10.11648/j.ijiis.20200902.11
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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