Diagnosis of acute lymphoblastic leukaemia using fuzzy logic and neural networks

Abstract

In this paper, we present an algorithm for diagnosis of acute lymphoblastic leukaemia (ALL) in developing countries like Mexico. The proposed method uses a robust fuzzy logic algorithm to classify the ALL using microscopic cell images obtained by smears of bone marrow aspirates. We improve the results of fuzzy method using a radial basis function neural network to realise the diagnosis.

Keywords:

• leukaemia
• fuzzy logic
• radial basis function neural network

The work is supported by the National Polytechnic Institute of Mexico (IPN), National Council on Science and Technology of Mexico (CONACYT) and Highly Specialized Central South Hospital of PEMEX.