Researchers at Shanghai Jiao Tong University have proposed a new method for lung image registration called Dlung, which is an unsupervised few-shot learning-based diffeomorphic lung image registration. This method can help construct respiratory motion models based on limited data with high speed and accuracy, offering an efficient method for respiratory motion modeling. This is important for targeting tumors by radiotherapy while avoiding damage to normal tissues during lung cancer treatment. Dlung solves the problem of limited data through fine-tuning techniques and realizes diffeomorphic registration by the scaling and squaring method, achieving the highest accuracy with diffeomorphic properties when applied in the registration of 4D images.
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A novel method for lung image registration
