Abstract
White blood cell cancer is additionally mentioned as leukemia could also be a really perilous disease. To this day, the tactic of recognizing white blood cell cancer or leukemia remains done conventionally, which if done by different doctors, can cause a difference within the diagnosis. To retort these problems, a computer-assisted method is proposed during which leukemia is detected from microscopic images employing a mixture of SVM and KNN. Initially, preprocessing is performed to arrange the image for processing. Later support vector machine (SVM) and K-nearest neighbor are used for classification. The proposed algorithm classifies healthy and cancerous cells into one of the four types such as acute lymphocytic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), and chronic myeloid leukemia (CML). Additionally, the counting of the infected cells is also performed.
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Santhosh Krishna, B.V., Jijin Godwin, J., Tharanee Shree, S., Sreenidhi, B., Abinaya, T. (2021). Detection of Leukemia and Its Types Using Combination of Support Vector Machine and K-Nearest Neighbors Algorithm. In: Kumar, R., Mishra, B.K., Pattnaik, P.K. (eds) Next Generation of Internet of Things. Lecture Notes in Networks and Systems, vol 201. Springer, Singapore. https://doi.org/10.1007/978-981-16-0666-3_35
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DOI: https://doi.org/10.1007/978-981-16-0666-3_35
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