Identification and classification of acute leukemia using neural network

Leukemia, a subdivision of cancer, develops in human blood and the bone marrow. The reason behind is the expeditious and sudden formation and accumulation of WBCs in blood. Identification & diagnosis of these types of abnormalities by humans is difficult and may lead to misidentification. Therefore an automatic system for the identification and classification would be of great help. This paper aims at proposing a technique for correct and quick classification of leukemia images and categorizing them into their respective types. For this, different features are extracted from the input images and then based on these features a data set for the input images is created. This data set is then utilized as input data to a neural network for training purposes. This neural network is designed and created to categorize the images according to their corresponding leukemia type.