Sannihitha Peetala, Dr B Leela Kumari
Leukemia or blood cancer is a life-threatening ailment of blood. It originates in bone marrow, & causes the formation of large number of abnormal cells. Leukemia is classified as Acute Lymphoblastic Leukemia (ALL), Acute Myeloid Leukemia (AML), Acute Myeloid Leukemia (ALL), Chronic Lymphatic Leukemia (CLL) &Chronic Myeloid Leukemia (CML). This Dissertation will aim at automated detection & staging of leukemia using combination of image processing &artificial intelligence technique. Also, detection of white blood in blood stain image, accurately, is crucial for prediction of leukemia with accuracy. This dissertation also aims of improving the accuracy of WBC detection using combination of contrast enhancement morphological area operation & Hough transform to find circles. WBC segmented by both the above methods. The outputs were then processed by Levenberg–Marquardt algorithm, which is pre trained with number of samples using artificial neural network to classify the blood stain as leukemia or non-leukemia and provide staging.
White Blood Cells, Leukemia, Microscopic images, Morphological area, Hough transform, Artificial neural networks
Cite this paper
Sannihitha Peetala, Dr B Leela Kumari. (2022) Detection of Leukemia & its Staging Using Image Processing; Artificial Intelligence . International Journal of Signal Processing, 7, 36-43