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

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IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|July 14, 2025

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InstantGroup efficiently generates groupwise medical image templates using variational autoencoder models. This framework offers scalable, fast template creation for any group size, improving registration accuracy.

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Area of Science:

Medical imaging
Computer vision
Machine learning

Background:

Groupwise image registration aligns multiple subjects into a common space.
Current template generation methods are time-consuming and lack scalability.
Efficient template generation is crucial for groupwise medical image analysis.

Purpose of the Study:

To develop an efficient and scalable framework for groupwise template generation.
To leverage latent space properties of variational autoencoder (VAE) models for template creation.
To improve template quality and registration accuracy in groupwise image analysis.

Main Methods:

Introduced InstantGroup, an efficient groupwise template generation framework using VAEs.
Employed a Dual VAE backbone with shared-weight twin networks.
Incorporated a Displacement Inversion Module (DIM) for template unbiasedness and a Subject-Template Alignment Module (STAM) for enhanced quality.

Main Results:

InstantGroup dramatically reduces template generation runtime, achieving results in seconds.
The framework demonstrates scalability to groups of any size.
Maintained superior performance in unbiasedness and registration accuracy compared to state-of-the-art methods.

Conclusions:

InstantGroup provides an efficient, scalable, and accurate solution for groupwise template generation.
The VAE-based approach with DIM and STAM modules enhances template quality and registration performance.
This framework significantly advances groupwise medical image registration capabilities.