Incorporating historical sub-optimal deep neural networks for dose prediction in radiotherapy

•The non-modulated dose distribution, which is the initial quantity of the inverse optimization phase in radiotherapy, is used as part of the input to aid the training of the segmentation-based network.•A novel ensemble method that takes advantages of the sub-optimal models during the historical training phase is used to improve the predictions on test data.•Empirical experiments demonstrate that the non-modulated dose distribution provides effective auxiliary information which facilitates the convergence of the network during the training phase. Moreover, the dose distribution predictions can be further improved by employing the HSE method.