A fuzzy neural network is an approach to mimic the structure and function of our brain. This method is widely applied in character recognition, but not in medical image recognition. The area of medical image recognition is challenging to our interest and can be maximally utilized the advantage of fuzzy neural networks in practice. In this paper we propose and new neural algorithm which is integrated both fuzzy self-organized and supervised learning methods. The proposed algorithm is applied for bronchogenic cancer diagnosis. The experimental results show that the correct recognition rate of our algorithm is superior to that of other neural networks.