This study proposes a novel segmentation algorithm for lung nodules detection in thorax computed tomography (CT). In order to decide, at each iteration, whether two adjacent objects should be merged or not, a region growing procedure calculates a heterogeneity growth based on multiple criteria. However, segmentation algorithm depends on some parameters which were found by genetic algorithm. Results produced by the proposed segmentation were closely consistent with the reference segments provided manually by an expert physician. The detection itself achieved 80,9% sensitivity with 0,23 false positive per slice which indicates that the proposed method is able to provide a good suggestion for the specialist. Results indicate the potential of proposed segmentation method and encourage a further investigation aiming at improving its accuracy.