Title: Acute Myeloid Leukemia Detection in WBC Cell Based on ICA Feature Extraction
Abstract: Leukemia Detection is planned in automatic advance. Such cancer is related to WBCs that affects the blood cells of body. Acute Myeloid leukemia is disease of the myeloid line of platelets described by the quick development of strange white platelets that development in the bone marrow. Generally acute leukemia influence adults and its affects maximizes with age. The symptoms of AML are occurred by replacement of genuine bone marrow by leukemia cells. A basic technique of LEUKAEMIA DETECTION, experts checks mini images. Leukemia identification delivers in the bone marrow. Leukemia is a kind of blood cancer. They develop quicker than ordinary cells, and they don’t break expanding while they should. Above time, leukemia cells can mass out the typical platelets. Each bone contains a thin material inside is perceived bone marrow. The small scale scopic pictures of the platelets are testing to discover numerous ailments. Varieties in the blood circumstance demonstrate the development of maladies in a substance. Leukemia would central be able to end in the event that it is left indistinct. In view of an amount of information it is built up. The instruments of erythrocytes and leukocytes and platelets. Initiallly Leukemia is diagnosed only by investigating white blood cells. Active on WBC, Leukemia Detection framework examines the microscopic image and overcome such problems. Significant parts of pictures are removed and some strategies applied directly. K-mean collecting applies only to detect WBC. Its an active area of research and many strategies are proposed till date on automated differential blood count. Several experts are still researching in this area as mechanized difference blood counting framework contributions in identification of various diseases. From the writing on leukocyte picture division it’s watched that the vast majority of plans push onto core extraction and not very many plans can extract the cytoplasm that too with lesser accuracy. In this research work, we implement the k-means clustering to identify the cell classification and ICA algorithm used for feature extraction algorithm and classifies the cancer detection and calculate the performance parameters like FAR, FRR and accuracy. Simulation tool used in this research work 2013a and compare the proposed performance parameters with existing parameters.
Publication Year: 2018
Publication Date: 2018-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 1
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