Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI

06/24/2021
by   Mengwei Ren, et al.
11

Current deep learning approaches for diffusion MRI modeling circumvent the need for densely-sampled diffusion-weighted images (DWIs) by directly predicting microstructural indices from sparsely-sampled DWIs. However, they implicitly make unrealistic assumptions of static q-space sampling during training and reconstruction. Further, such approaches can restrict downstream usage of variably sampled DWIs for usages including the estimation of microstructural indices or tractography. We propose a generative adversarial translation framework for high-quality DWI synthesis with arbitrary q-space sampling given commonly acquired structural images (e.g., B0, T1, T2). Our translation network linearly modulates its internal representations conditioned on continuous q-space information, thus removing the need for fixed sampling schemes. Moreover, this approach enables downstream estimation of high-quality microstructural maps from arbitrarily subsampled DWIs, which may be particularly important in cases with sparsely sampled DWIs. Across several recent methodologies, the proposed approach yields improved DWI synthesis accuracy and fidelity with enhanced downstream utility as quantified by the accuracy of scalar microstructure indices estimated from the synthesized images. Code is available at https://github.com/mengweiren/q-space-conditioned-dwi-synthesis.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 6

page 8

page 9

page 13

08/12/2021

Multi-Modal MRI Reconstruction with Spatial Alignment Network

In clinical practice, magnetic resonance imaging (MRI) with multiple con...
09/12/2021

Prioritized Subnet Sampling for Resource-Adaptive Supernet Training

A resource-adaptive supernet adjusts its subnets for inference to fit th...
10/05/2018

Generating Diffusion MRI scalar maps from T1 weighted images using generative adversarial networks

Diffusion magnetic resonance imaging (diffusion MRI) is a non-invasive m...
11/29/2020

Semi-Supervised Learning of Mutually Accelerated Multi-Contrast MRI Synthesis without Fully-Sampled Ground-Truths

This study proposes a novel semi-supervised learning framework for mutua...
02/05/2018

Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networks

Acquiring images of the same anatomy with multiple different contrasts i...
10/24/2019

Knowledge Transfer between Datasets for Learning-based Tissue Microstructure Estimation

Learning-based approaches, especially those based on deep networks, have...
01/05/2018

Learning Implicit Brain MRI Manifolds with Deep Learning

An important task in image processing and neuroimaging is to extract qua...

Code Repositories

q-space-conditioned-dwi-synthesis

None


view repo
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.