Recognition of Blood Cancer Using Different Classification Techniques
DOI:
https://doi.org/10.62760/iteecs.1.1.2022.4Keywords:
Blood cancer detection, C-Means clustering, K-Means clustering, Genetic algorithmAbstract
Several image processing methods or applications have been established to get the requisite details from microscopic images for the fast and cost effective development of patient diagnosis. A type of leukemia that is more frequent in children is Acute Lymphoblastic Leukemia (ALL). The word 'Acute' suggests that leukemia can develop rapidly and can lead to fatal death within a few months if not managed. Because of its nonspecific existence, erroneous diagnosis refers to the effects and manifestations of everything. And though it is challenging for hematologists to identify leukemia cells, manual sorting of blood cells is not only time-consuming but also unreliable. Consequently, early diagnosis of leukemia helps in presenting the patient with the necessary care. The mechanism recommends individuals in the blood picture the leucocytes from the blood cells as a response to this issue, and then select the lymphocyte cells. The morphological index of certain cells is measured and the involvement of leukemia is eventually classified. A literature review on several methods used to identify cancer cells has been carried out in this article.
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