Comparison of Feedforward Network and Radial Basis Function to Detect Leukemia

L is one of the many types of cancers. Leukemia is caused in the white blood cells near the bone marrow region of our body. In this the white blood cells (WBCs) which get infected turns blue. Like any other cancer in this also the cell divides itself at the faster pace. Even when it is not required they multiply causing a tumor. Detected and treated at an early stage of leukemia saves a lot of lives. According to leukemia research foundation, every four minutes someone is diagnosed with leukemia. More than 176,000 are expected in U.S. Leukemia helps in detecting blood cancer using two basic modules of image processing i.e. Image segmentation and feature extraction. After these two modules we use two techniques of neural network i.e. feed forward network and radial basis function network (RBFNN) for the detection purposes. We compare the accuracy percentage in both of them. The technique with best accuracy percentage is recorded as the more efficient technique.