An unsupervised deep learning method for affine registration of multi-contrast brain MR images

作者：Srivathsa Pasumarthi Venkata, Ben A. Duffy, Keshav Datta · 发表于：Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 年份：2023 · DOI：10.58530/2022/0168 · 研究领域：Medical Image Segmentation Techniques、Advanced MRI Techniques and Applications、Medical Imaging Techniques and Applications

Image registration is a crucial preprocessing step for many downstream analysis tasks. Existing iterative methods for affine registration are accurate but time consuming. We propose a deep learning (DL) based unsupervised affine registration algorithm that executes orders of magnitude faster when compared to conventional registration toolkits. The proposed algorithm aligns 3D volumes from the same modality (e.g. T1 vs T1-CE) as well as different modalities (e.g. T1 vs T2). We train the model and perform quantitative evaluation using a pre-registered brain MRI public dataset.