Presented in this paper is a neural back propagation algorithm for reconstructing two-dimensional CT images from a small number of projection data. The paper extends the work in [1], in which a backpropagation algorithm is applied to the CT image reconstruction problem. The delta rule of the ordinary backpropagation algorithm is modified using a 'secondary' teaching signal and the 'Resilient backpropagation' scheme. Results obtained are presented along with those of two well known conventional methods: MART and EMML method. A quantitative evaluation reveals the effectiveness of the proposed algorithm.