Adaptive Neuro Fuzzy Inference System for White Blood Cell Classification
2nd International Conference on Innovative Research in Engineering and Technology (iCIRET2013), January 3-5, 2013
6 Pages Posted: 3 Oct 2013
Date Written: January 4, 2013
Abstract
This paper describes the practical application of Adaptive Neuro-Fuzzy Inference System (ANFIS) framework for classification of white blood cells. Differential count of the several types of white blood cells (WBC) in bone marrow smears is applied to assist find infection, anemia and leukemia or to observe the process of treatment. In this paper we represent a fuzzy Inference system approach to discover edge inside color bone marrow microscopic pictures, to get a solution for iteration level for image processing. In this paper, we investigate whether selective information about the nucleus only is sufficient to classify white blood cells. This is essential because partitioning of nucleus is very much simpler than the partitioning of the total cell, particularly in the bone marrow where the white blood cell density is really high.
Keywords: Anfis, white Blood Cells, Fuzzy Logic, Neural Network, Segmentation, Classification
Suggested Citation: Suggested Citation