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Izvorni znanstveni članak
https://doi.org/10.20532/cit.2018.1004123

A Framework for Efficient Recognition and Classification of Acute Lymphoblastic Leukemia with a Novel Customized-Knn Classifier

Duraiswamy Umamaheswari   ORCID icon orcid.org/0000-0002-7110-0610 ; Vidyasagar College of Arts and Science, Udumalpet, Tamil Nadu
Shanmugam Geetha ; Vidyasagar College of Arts and Science, Udumalpet, Tamil Nadu

Puni tekst: engleski, pdf (968 KB) str. 131-140 preuzimanja: 251* citiraj
APA 6th Edition
Umamaheswari, D. i Geetha, S. (2018). A Framework for Efficient Recognition and Classification of Acute Lymphoblastic Leukemia with a Novel Customized-Knn Classifier. Journal of computing and information technology, 26 (2), 131-140. https://doi.org/10.20532/cit.2018.1004123
MLA 8th Edition
Umamaheswari, Duraiswamy i Shanmugam Geetha. "A Framework for Efficient Recognition and Classification of Acute Lymphoblastic Leukemia with a Novel Customized-Knn Classifier." Journal of computing and information technology, vol. 26, br. 2, 2018, str. 131-140. https://doi.org/10.20532/cit.2018.1004123. Citirano 25.02.2021.
Chicago 17th Edition
Umamaheswari, Duraiswamy i Shanmugam Geetha. "A Framework for Efficient Recognition and Classification of Acute Lymphoblastic Leukemia with a Novel Customized-Knn Classifier." Journal of computing and information technology 26, br. 2 (2018): 131-140. https://doi.org/10.20532/cit.2018.1004123
Harvard
Umamaheswari, D., i Geetha, S. (2018). 'A Framework for Efficient Recognition and Classification of Acute Lymphoblastic Leukemia with a Novel Customized-Knn Classifier', Journal of computing and information technology, 26(2), str. 131-140. https://doi.org/10.20532/cit.2018.1004123
Vancouver
Umamaheswari D, Geetha S. A Framework for Efficient Recognition and Classification of Acute Lymphoblastic Leukemia with a Novel Customized-Knn Classifier. Journal of computing and information technology [Internet]. 2018 [pristupljeno 25.02.2021.];26(2):131-140. https://doi.org/10.20532/cit.2018.1004123
IEEE
D. Umamaheswari i S. Geetha, "A Framework for Efficient Recognition and Classification of Acute Lymphoblastic Leukemia with a Novel Customized-Knn Classifier", Journal of computing and information technology, vol.26, br. 2, str. 131-140, 2018. [Online]. https://doi.org/10.20532/cit.2018.1004123

Sažetak
Even in this modern era today, life's extent is still being challenged by many pathological diseases such as cancer. One such hazard is leukemia. Even a trivial setback in detecting leukemia lead to a severe outcome: the affected cells may eventually prove to be fatal. To combat this, we propose an algorithm to better segment the nucleus region of White Blood Cells (WBC) found in stained blood smear images with the intent of identifying Acute Lymphoblastic Leukemia (ALL). In our proposal, the image is made ready for segmentation in the preprocessing stage by changing its size, brightness, and contrast. In the segmentation stage, the nucleus region is segmented by mathematical operators and Otsu's thresholding. Then mathematical morphological operators are applied in post-processing stage, which makes the nucleus region convenient for feature extraction. Finally, the segmented regions are classified into ALL affected and regular cells by means of the proposed Customized K-Nearest Neighbor classifier algorithm. This work was experimented with over 80 images of the ALL-IDB2 dataset and attained an accuracy rate of 96.25%, 95% of sensitivity and 97% of specificity.

Ključne riječi
acute lymphoblastic leukemia; KNN classifier; morphology; segmentation; WBC

Hrčak ID: 207058

URI
https://hrcak.srce.hr/207058

Posjeta: 392 *