Acute Lymphocytic Leukemia Detection from Blood Microscopic Images
International Journal of Engineering Research and
The classification of blood cells is important for the evaluation and diagnosis of many diseases in medical diagnosis systems. Acute Lymphocytic Leukemia (ALL) is a type of childhood blood cancer and is mostly seen in children below 7-8 years. It can be dangerous if left untreated and causes death. Detection of ALL can be done through the analysis of white blood cells (WBCs) also called as leukocytes. Usually the analysis of blood cells is performed manually by skilled operators. This manual
... ors. This manual techniques have numerous drawbacks, such as slow analysis and a non-standard accuracy. It all depends on the skill of the operator. Hence many automated systems are using in order to analyze and classify the blood cells, but most of which produces only partial results. The main steps of this work are image preprocessing, WBC extraction, separation of adjacent WBCs, feature extraction and classification. Image preprocessing is done by converting RGB images into Lab color space images. It is done to enhance the visual appearance of the image and to reduce the memory requirements. Then the WBCs are identified by using fuzzy C means clustering algorithm. Adjacent WBCs are a major challenge while performing the feature extraction in the later stages. For avoiding that, separation of adjacent leukocytes is done by using Marker based watershed segmentation. For feature extraction, the features of WBC such as area, energy, entropy etc. are considered. To detect whether the patient is leukemic or not, a neuro -fuzzy classifier is used.