An artificial neural network ensemble is a learning paradigm where several artificial neural networks are jointly used to solve a problem. In this paper, an automatic pathological diagnosis procedure named Neural Ensemble-based Detection (NED) is proposed, which utilizes an artificial neural network ensemble to identify lung cancer cells. The neural algorithm we used is FANNC, which is a fast adaptive neural classifier that performs one-pass incremental learning with fast speed and high accuracy.  The fundamental operation of the artificial neural network is local two-dimensional convolution rather than full connection with weighted multiplication. Weighting coefficients of the convolution kernels are formed by the artificial neural network through back propagated training.  The artificial convolution neural network acted as a final classifier to determine whether the suspected image block contains a lung nodule.

By: VIJAYALAKSHMI .A  (FINAL -Yr, B.E)
      VINODHINI .K (FINAL-Yr, B.E)

      MAHENDRA ENGINEERING COLLEGE FOR WOMEN, KUMARAMANGALAM

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