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.
| Published in | International Journal of Intelligent Information Systems (Volume 9, Issue 2) |
| DOI | 10.11648/j.ijiis.20200902.11 |
| Page(s) | 6-15 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2020. Published by Science Publishing Group |
Image Processing, Acute Lymphoblastic Leukemia, ALL, Blood Cancer, Image Segmentation, Performance, Efficiency
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APA Style
Saif Ali, Aneeqa Tanveer, Azhar Hussain, Saif Ur Rehman. (2020). Identification of Cancer Disease Using Image Processing Approahes. International Journal of Intelligent Information Systems, 9(2), 6-15. https://doi.org/10.11648/j.ijiis.20200902.11
ACS Style
Saif Ali; Aneeqa Tanveer; Azhar Hussain; Saif Ur Rehman. Identification of Cancer Disease Using Image Processing Approahes. Int. J. Intell. Inf. Syst. 2020, 9(2), 6-15. doi: 10.11648/j.ijiis.20200902.11
AMA Style
Saif Ali, Aneeqa Tanveer, Azhar Hussain, Saif Ur Rehman. Identification of Cancer Disease Using Image Processing Approahes. Int J Intell Inf Syst. 2020;9(2):6-15. doi: 10.11648/j.ijiis.20200902.11
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Download@article{10.11648/j.ijiis.20200902.11,
author = {Saif Ali and Aneeqa Tanveer and Azhar Hussain and Saif Ur Rehman},
title = {Identification of Cancer Disease Using Image Processing Approahes},
journal = {International Journal of Intelligent Information Systems},
volume = {9},
number = {2},
pages = {6-15},
doi = {10.11648/j.ijiis.20200902.11},
url = {https://doi.org/10.11648/j.ijiis.20200902.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20200902.11},
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.},
year = {2020}
}
TY - JOUR T1 - Identification of Cancer Disease Using Image Processing Approahes AU - Saif Ali AU - Aneeqa Tanveer AU - Azhar Hussain AU - Saif Ur Rehman Y1 - 2020/07/04 PY - 2020 N1 - https://doi.org/10.11648/j.ijiis.20200902.11 DO - 10.11648/j.ijiis.20200902.11 T2 - International Journal of Intelligent Information Systems JF - International Journal of Intelligent Information Systems JO - International Journal of Intelligent Information Systems SP - 6 EP - 15 PB - Science Publishing Group SN - 2328-7683 UR - https://doi.org/10.11648/j.ijiis.20200902.11 AB - 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. VL - 9 IS - 2 ER -
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