Automated Detection of White Blood Cells Cancer Disease

Lakshmi Kg, N. Manja Naik
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引用次数: 5

Abstract

Leukemia is a blood disease . The pace of cure be dependent upon the kind of Leukemia just as the period of unfortunate casualties. Intense lymphocytic Leukemia, Acute myeloid Leukemia and typical instances of Microscopic pictures of blood marrow spreads at first separated the core by evacuating foundation utilizing division. At that point the impacted cores' shading, GLCM and geometric highlights are separated lastly these cells are named carcinogenic or nonmalignant cell and its subtypes utilizing bolster vector machine (SVM) and KNN classifier. The precision of the classifier assessed up to 94.3%. The trial results demonstrates that proposed calculation could achieve a sufficient exhibition for the analysis of AML, ALL and their sub-types.
白细胞癌疾病的自动检测
白血病是一种血液疾病。治愈的速度取决于白血病的种类,就像不幸伤亡的时间一样。强烈淋巴细胞白血病、急性髓性白血病及典型的骨髓扩散显微镜图片,首先利用分裂抽离基础分离核心。然后对影响核的阴影、GLCM和几何高光进行分离,最后利用支撑向量机(SVM)和KNN分类器将这些细胞命名为致癌细胞或非恶性细胞及其亚型。分类器的准确率达到94.3%。实验结果表明,所提出的计算方法能够达到AML、ALL及其亚型分析的充分展示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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