AUTOMATED SCREENING SYSTEM FOR ACUTE MYELOGENOUS LEUKEMIA DETECTION

Abstract : Acute myelogenous leukemia (AML) is a subtype of acute leukemia, which is prevalent among adults.The average age of a person with AML is 65 years. The need for automation of leukemia detection arises since current methods involve manual examination of the blood smear as the first step toward diagnosis. This is time-consuming, and its accuracy depends on the operator’s ability. In this paper, a simple technique that automatically detects and segments AML in blood smears is presented.

 EXISTING SYSTEM :

 ? Two new features, such as cell energy and Hausdorff dimension (HD), have been used. The result is then compared with the results of the existing models ? The LBP method has proved to outperform many existing methods, including the linear discriminant analysis and the principal component analysis. ? The system presented not only enables classification of whole images but also presents a better performance for subimages when compared with some of the existing systems ? A set of four existing systems that employ the same color correlation, segmentation, and classification techniques as the proposed system were taken into consideration

 DISADVANTAGE :

 ? This speaks to the difficulty in designing a general-purpose clustering algorithm and the ill-posed problem of clustering ? The selection of a classification technique for classification is a challenging problem because an appropriate choice given the available data can significantly help improving the accuracy in credit scoring practice.

 PROPOSED SYSTEM :

 ? The proposed system attempts to present an effective tool that acts as an ancillary to the physicians in decision-making. ? A watershed segmentation algorithm to segment nucleus from the surrounding cytoplasm of cervical cancer images was proposed by Nallaperumal and Krishnaveni ? This paper is structured as follows. Section II focuses in detail on the process overview of the proposed model. Sections III and IV show the image processing methods being used to perform enhancement and segmentation. Section V builds the database of future vectors, which are used by the classification component of the system.

 ADVANTAGE :

 ? The constructed system is applied to complete blood smear images containing multiple nuclei. Two new features, such as cell energy and Hausdorff dimension (HD), have been used. ? Third, it has only two color components (a and b), and it is designed to approximate human vision (the L component closely matches human perception of lightness or it can be used to adjust the lightness contrast using the L component. ? It was noted that certain features were widely used as they gave a good classification.

Deep Learning Covid-19 outbreak

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MACHINE LEARNING AUTOMATED SCREENING SYSTEM