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Template generation is a critical step in groupwise image registration, whichinvolves aligning a group of subjects into a common space. While existingmethods can generate high-quality template images, they often incur substantialtime costs or are limited by fixed group scales. In this paper, we presentInstantGroup, an efficient groupwise template generation framework based onvariational autoencoder (VAE) models that leverage latent representations'arithmetic properties, enabling scalability to groups of any size. InstantGroupfeatures a Dual VAEs backbone with shared-weight twin networks to handle pairsof inputs and incorporates a Displacement Inversion Module (DIM) to maintaintemplate unbiasedness and a Subject-Template Alignment Module (STAM) to improvetemplate quality and registration accuracy. Experiments on 3D brain MRI scansfrom the OASIS and ADNI datasets reveal that InstantGroup dramatically reducesruntime, generating templates within seconds for various group sizes whilemaintaining superior performance compared to state-of-the-art baselines onquantitative metrics, including unbiasedness and registration accuracy.

InstantGroup: Instant Template Generation for Scalable Group of Brain MRI Registration