We consider the automatic hardness determination of a chest X-ray image and the effect of pre-filtering of the training and validation samples on the performance of the classification algorithm of tuberculosis diagnosis from chest X-rays. Convolutional neural networks are used in automatic hardness determination and tuberculosis diagnosis. The results of the present study are compared with those from different datasets, including datasets pruned by image hardness criteria.