Motion Artifacts Reduction Algorithm Application for 4D MR Images

4D MR images have been playing an important role in tumor target definition in treatment planning and tumor motion assessment during radiation therapy. To reduce motion artifacts caused by respiratory motion and further improve image quality, an effective method based on combined linear polynomial fitting and principal component analysis was proposed to remodel displacement vector fields (DVFs) of original 4D-MRI, and the reference image was then deformed using the new DVFs to acquire 4D MR images without or reduced motion artifacts in this study. The distorted regions around the diaphragm and tumor were mitigated and maintained original motion pattern in the synthetic 4D MR images. The consistency of two measurements and the qualitative analysis of results show that the proposed algorithm can improve the image quality of 4D MR images on the basis of keeping original motion pattern, which provids good conditions for precise tumor radiation therapy.