Multiscale Metamorphic VAE for 3D Brain MRI Synthesis

• URL: http://arxiv.org/abs/2301.03588v2
• Date: Wed, 11 Jan 2023 05:34:35 GMT
• Title: Multiscale Metamorphic VAE for 3D Brain MRI Synthesis
• Authors: Jaivardhan Kapoor, Jakob H. Macke, Christian F. Baumgartner
• Abstract summary: Generative modeling of 3D brain MRIs presents difficulties in achieving high visual fidelity while ensuring sufficient coverage of the data distribution. In this work, we propose to address this challenge with composable, multiscale morphological transformations in a variational autoencoder framework. We show substantial performance improvements in FID while retaining comparable, or superior, reconstruction quality compared to prior work based on VAEs and generative adversarial networks (GANs)
• Score: 5.060516201839319
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Generative modeling of 3D brain MRIs presents difficulties in achieving high visual fidelity while ensuring sufficient coverage of the data distribution. In this work, we propose to address this challenge with composable, multiscale morphological transformations in a variational autoencoder (VAE) framework. These transformations are applied to a chosen reference brain image to generate MRI volumes, equipping the model with strong anatomical inductive biases. We structure the VAE latent space in a way such that the model covers the data distribution sufficiently well. We show substantial performance improvements in FID while retaining comparable, or superior, reconstruction quality compared to prior work based on VAEs and generative adversarial networks (GANs).

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