Retrospective 4D image construction from continuously acquired 2D slices is a necessary step to achieve high-quality 4D images. Self-gating methods, which extract breathing signals only from image information without any external gating technology, have much potential, such as in pediatric patients with thoracic insufficiency syndrome (TIS) who suffer from extreme malformations of the chest wall, diaphragm, and spine, leading to breathing that is very complex with lots of abnormal respiration cycles, including very deep or shallow cycles. Existing methods do not work well in this clinical scenario and most are not fully automatic, requiring some manual interactive operations. In this paper, we propose a fully automatic 4D dMRI construction method based on the concept of flux to address the 4D image construction from 2D slices of subjects with complex respiration. Firstly, we extract the breathing signal for each location based on the flux of the optical flow vector field of the body region from the image series. Then, we give a full analysis for all cycles and extract several normal ones and map them to one cosine respiration model for each location. After that, we re-sample one normal cycle from the respiration model for each location independently. All of these resampled normal cycles form the final constructed 4D image. Qualitative and quantitative evaluations on 25 subjects show that the proposed method can handle datasets from subjects with more complex respiration and achieves good self consistency results while maintaining time and space continuity.